Navigating the complexities of our future is big business – and big money. Here are some of the more eminent global futurists offering fresh insights into future tech and a better tomorrow.



At the South by Southwest (SXSW) festival in Austin, Texas, there’s one particular session where people start queueing around four in the morning to get a seat. It’s not one of the big-name music performances or a movie screening with awards buzz, it’s a keynote by Amy Webb.



Webb, who is the founder and CEO of the Future Today Institute (FTI), is a futurist. She’s a professor of strategic foresight, a data and research-driven field that unpacks what could be in an increasingly complex world. Webb’s 2024 Tech Trends Report, which is downloaded more than a million times every year, is made up of just under a thou- sand pages of insights businesses rely on to navigate the future.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
IN HER TALK AT SXSW, AMY WEBB SAID THAT THE NEXT STAGE OF AI IS MERGING DIGITAL SUPERCOMPUTERS WITH HUMAN TISSUE. THIS IS SOMETHING WEBB REFERS TO AS ORGANOID INTELLIGENCE, OR O-AI. SHE PREDICTS THAT BY 2039, O-AI WILL BECOME THE FOREFRONT OF COMPUTATIONAL EVOLUTION, MERGING HUMAN-LIKE DECISION-MAKING CAPABILITIES WITH THE SPEED OF TRADITIONAL COMPUTERS. IN SIMPLE TERMS, WEBB SAYS THAT WE WILL BE ABLE TO MAKE BIOCOMPUTERS OUT OF HUMAN BRAIN CELLS – WE WILL GROW COMPUTERS RATHER THAN BUILD THEM.
</blockquote>



Predicting what comes next may be big business but it’s not necessarily new. While modern futurists use data to forecast pos- sible future scenarios and spot emerging opportunities, the science of probability – long-term planning – has been around since the 1940s. And before futurology became an academic field and job role, science fiction authors like H.G. Wells, Jules Verne and Arthur C. Clarke, were recognized as futurists with an uncanny ability to foresee the world to come. Today, there are a number of well-known futurists sought out by industry giants (and the government) to steer business strategy and adapt to disruptive change. Businesses are hiring futurists to tell them the things they don’t want to hear so that they can prepare for unfore- seen inevitabilities.



Meet the futurists



As the founder of Singularity University and the XPRIZE Foundation, Peter Diamandis is a Silicon Valley digital futurist and engineer who has started over 25 companies. Now in his 60s, Diamandis (whose net worth has been reported to be around $200 million) has many innova- tive projects underway. While tickets to attend his membership-only Abundance Summit begin at $10,000, Diamandis is attempting to change the world with his large-scale XPRIZE competitions that tackle domains like climate, space, biodiversity and deep tech. According to the Key Speakers Bureau, Diamandis’ speaking fee starts at $60,000 – and that’s for a virtual, not in-person, appearance.



As artificial intelligence (AI) becomes more and more popular, there’s a good chance that futurist Ray Kurzweil will be mentioned. Kurzweil, who has received 20 honorary doctorates is a computer scientist and futurist with a 30-year track record of accurate predic- tions – his written predictions, of which there are 147, have an 86% accuracy rate. Kurzweil’s first predictions around AI came out in 1999 and while many people felt that his views were radical when he said that computers would be as intelligent as humans, his estimated date of 2029 doesn’t seem so far off. Kurzweil’s net worth is reportedly around $30 million, most of which comes from the four companies he success- fully founded based on his research and academic prizes. One of his boldest predictions is that immortality will be achievable by 2030 with nanobots – tiny robots that can repair human bodies on a cellular level.



In an interview, he famously said: “By the time we get to the 2040s, we’ll be able to multiply human intelligence a billionfold. That will be a profound change that’s singular in nature. Computers are going to keep getting smaller and smaller. Ultimately, they will go inside our bodies and brains and make us healthier, make us smarter.”



Webb, who has been called ‘one of the five women changing the world’, recently wrote a book called The Genesis Machine with fellow futurist, Andrew Hessel. The book, which won a Gold Axiom Medal, explores synthetic biology, a controversial and emerging techno-science. Biotech, which is something both Webb and Hessel focus on, was a key part of Webb’s 2024 Tech Trends Report. In her talk at SXSW, she said that the next stage of AI is merging digital supercomputers with human tissue. This is something Webb refers to as organoid intelligence, or O-AI. She predicts that by 2039, O-AI will become the forefront of computational evolution, merging human-like decision-making capabilities with the speed of traditional computers. 



In simple terms, Webb says that we will be able to make biocomputers out of human brain cells – we will grow computers rather than build them. Hessel is a pioneer in synthetic biology, microbiologist, geneticist and futurist. He is also the co-founder of a company called Hu-mane Genomics Inc. that engineers synthetic viruses to target cancer cells. “Biology is a very different medium than computing but there are fundamental similarities,” he wrote in a blog post talking about synthetic biology in Af-rica. “Africa is geographically well-positioned to benefit from synthetic biology. Much of the country is in the biological power band of the world, blessed with ample sunlight, fresh water, fertile soils, and incredible biological diversity. But it is also vulnerable to changes in climate, particularly shifts in rainfall and heat waves,” he continues. Hessel has seen first-hand how AI tools are supercharging all aspects of digital biology and predicts that DNA printers are on the cusp of a major upgrade. He believes that in the next five years, we will be able to print and assemble microbial-scale genomes — at reasonable cost and turnaround times.



In the workplace



No matter whether you call them futurists, fu-turologists, foresight practitioners or horizon scanners, it’s becoming increasingly common for organizations to employ professionals with these titles. According to the Univer-sity of Houston, around 25% of Fortune 500 companies have futurists on staff. They’re also commonplace at government agencies as well as non-profits. Andrew Bolwell, for example, is HP’s chief disrupter. In his role, he unpacks megatrends like microfluidics – working with tiny amounts of fluid with precision. Even though printers already do this, Bolwell is talking about even smaller amounts, fluids the fifth of a size of a human cell (or a thousand times smaller than a raindrop). With the microfluidics market projected to be worth $64.94 billion by 2029, according to Mordor Intelligence, the possibility of 3D-printing vital organs may become a reality.



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&#8220;BY THE TIME WE GET TO THE 2040S, WE’LL BE ABLE TO MULTIPLY HUMAN INTELLIGENCE A BILLIONFOLD. THAT WILL BE A PROFOUND CHANGE THAT’S SINGULAR IN NATURE. COMPUTERS ARE GOING TO KEEP GETTING SMALLER AND SMALLER. ULTIMATELY, THEY WILL GO INSIDE OUR BODIES AND BRAINS AND MAKE US HEALTHIER, MAKE US SMARTER.”&#8211; Ray Kurzweil
</blockquote>



When Dr Werner Vogels, Chief Technology Officer (CTO) and Vice President at Amazon, one of the globe’s most innovative companies, looks into the future, the world takes note.



The well-known futurist, who releases tech predictions for the year and beyond, also happens to be one of the highest-paid CTOs worldwide – it’s no wonder his live speaking fee reportedly starts at $100,000. One of Vo-gels’ predictions is that women’s healthcare, femtech, is on the rise. “Women’s healthcare is not a niche market,” he writes in his tech predictions report. “At AWS, we’ve been work-ing closely with women-led startups and have seen first-hand the growth in femtech. In the last year alone, funding has increased 197%.” 



With increased access to capital, technologies like machine learning, and connected devices designed specifically for women, Vogels believes that the world is at the precipice of an unprecedented shift, not only in the way women’s care is perceived, but how it’s administered. From women in rural areas who have been historically underserved medically to female athletes whose training was modelled on what worked for men, femtech will finally see women’s care move from the fringes to the forefront.



As companies strive to achieve aggressive sustainability targets, there are now climate and environmental futurists emerging as key strategic advisors, guiding businesses in navigating the complexities of climate change, resource management and eco-friendly practices to secure long-term viability and environmental stewardship. For Gerd Leonhard, a German futurist, green has become the new digital and sustainable is the new profitable. In a recent keynote, he said that he’s optimistic about climate change and global warming because we already have the tools we need to solve it. “We’re going to suffer for 15 to 20 years in the process of fixing this,” he predicts, “but we’re now getting ready to do this… technological advancements offer solutions that can help tackle these challenges. It will be essential to find a balance between economic progress and environmental preservation.”



Leonhard, like other consulting futurists, is working with companies to help them understand the next decade and develop foresight. “It’s not predictions, it’s understanding, intuition and imagination,” he explains in a podcast, adding that being a futurist is similar to being a therapist. His job is to essentially point his clients in the right direction; clients who happen to be tech giants, business leaders and government officials around the globe.



The future, today



There’s no question that history is happening now and futurists provide a way to understand current trends as well as anticipate what’s to come. Futurism is essentially risk management because every industry is experiencing dynamic change. In the last 50 years we’ve made more progress than in the previous 250,000 years and it’s been said that the next 10 years will bring more change than the previous 100. Of course, the future is unpredictable and futurists are not fortune tellers – they get things wrong. However, their value lies in their ability to analyze data and identify patterns. By incorporating foresight into strategic planning, businesses, governments and other organizations can adapt more effectively to emerging trends, mitigate risks and seize the moment. In a world characterized by rapid technological advancements, the role of the futurist has become increasingly indispensable in shaping a better tomorrow.

GUI (Graphical User Interface) concept.

The Fortune Of Foresight: Futurists On Tomorrow’s Tech

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



With companies like OpenAI, Google and Meta dropping increasingly sophisticated artificial intelligence products, crowdsourced rankings have emerged as a popular—and virtually only practical—way of determining which tool works best, and LMSYS’s Chatbot Arena has become possibly the most influential real-time gauge.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



While most organizations choose to measure their AI models against a set of general capability benchmarks that cover tasks like solving math problems, programming challenges or answering multiple choice questions across an array of university-level disciplines, there is no industry benchmark or standard practice for assessing large language models (LLMs) like OpenAI’s GPT-4o, Meta’s Llama 3, Google’s Gemini and&nbsp;<a href="https://www.forbes.com/sites/roberthart/2024/06/26/anthropics-claude-what-to-know-about-chatgpt-rival-after-latest-model-trounces-industry-giants/">Anthropic’s Claude</a>.



Even small differences to factors like datasets, prompts and formatting can have a huge impact on how a model performs, and when companies choose their own evaluation criteria, it can make it hard to fairly compare LLMs, Jesse Dodge, a senior scientist at the Allen Institute for AI in Seattle, told Forbes.



The difficulty in comparing LLMs is magnified given how closely leading models score on many commonly used benchmarks, with some companies and tech executives&nbsp;<a href="https://x.com/Ahmad_Al_Dahle/status/1780993216118210899" rel="noreferrer noopener" target="_blank">claiming</a>&nbsp;<a href="https://x.com/AnthropicAI/status/1803790676988920098" rel="noreferrer noopener" target="_blank">victory</a>&nbsp;over rivals with differences as narrow as 0.1%., so close it would likely go unnoticed by everyday users.



Community-built leaderboards deploying human insight have emerged, and in recent years their popularity has exploded in step with the steady boom of new AI tools like ChatGPT, Claude, Gemini and Mistral.



<a href="https://chat.lmsys.org/?leaderboard" rel="noreferrer noopener" target="_blank">The Chatbot Arena</a>, an open source project built by research group&nbsp;<a href="https://lmsys.org/about/" rel="noreferrer noopener" target="_blank">LMSYS</a>&nbsp;and the University of California, Berkeley’s Sky Computing Lab, has proven particularly popular and has built AI leaderboards by asking visitors to compare responses from two anonymous AI models and vote which one is best.



Its scoreboards rank more than 100 AI models based on nearly 1.5 million human votes so far, covering an array of categories including long queries, coding, instruction following, maths, “hard prompts” and a variety of languages including English, French, Chinese, Japanese and Korean.



<h2 class="wp-block-heading" id="h-what-s-the-best-ai-model-on-chatbot-arena">WHAT’S THE BEST AI MODEL ON CHATBOT ARENA?</h2>



The top five AI models on Chatbot Arena’s overall leaderboard are:



<ol class="wp-block-list">
<li>GPT-4o</li>



<li>Claude 3.5 Sonnet</li>



<li>Gemini Advanced</li>



<li>Gemini 1.5 Pro</li>



<li>GPT-4 Turbo</li>
</ol>



<h2 class="wp-block-heading" id="h-what-to-watch-for">WHAT TO WATCH FOR</h2>



Figuring out how to evaluate AI models is set to become increasingly important as more AI tools are rolled out and adopted across society. While benchmarks are important, Vanessa Parli, director of research at Stanford University’s Institute for Human-Centered AI, told Forbes they are also important as “goals for researchers to hit when developing models.” It is important to remember that “not all human capabilities are quantifiable” in a way that we can accurately measure but are nonetheless desirable to have in AI models, Parli said. There is also a clear need for benchmarks to assess traits like “bias, toxicity, truthfulness and other responsibility aspects,” especially for organizations dealing with sensitive information like healthcare companies, Parli said.



<h2 class="wp-block-heading" id="h-crucial-quote">CRUCIAL QUOTE</h2>



“The benchmarks aren’t perfect, but as of right now, that’s the primary mechanism we have to evaluate the models,” Parli told Forbes, cautioning that “researchers can somewhat easily game the system” today, with AI models quickly saturating benchmarks. “I think we need to get creative in the development of new ways to evaluate AI models,” Parli said. “



<h2 class="wp-block-heading" id="h-what-we-don-t-know">WHAT WE DON’T KNOW</h2>



Measuring intelligence is tricky when we do not know what it is we are supposed to be measuring. There is no universally accepted definition of intelligence in humans, let alone a way to measure it, and the possibility, nature and scope of animal intelligence has divided scientists for centuries. While AI benchmarks have typically focused on the ability to perform a particular task, more general assessments will be required in the near future as researchers make progress towards their goal of creating artificial general intelligence (AGI). AGI is capable of excelling and possibly matching humans across a broad set of domains rather than at just one task such as walking, moving boxes, identifying tumors on scans and playing chess.



<h2 class="wp-block-heading" id="h-how-useful-is-chatbot-arena-for-evaluating-ai-models">HOW USEFUL IS CHATBOT ARENA FOR EVALUATING AI MODELS?</h2>



“The rankings [Chatbot Arena] gives are something that I trust more than most other rankings,” Dodge told Forbes, “because it uses a real human to say whether they prefer one generation over another.” Parli suggested assessments like Chatbot Arena could “implicitly evaluate factors” we want in our AI but are less quantifiable than something like coding ability. But she did stress that something like Chatbot Arena should not be the only evaluation method used, saying there are “many factors that should be important to organizations when evaluating models” and it “does not cover all of them.”



.

Einstein And Musk Chatbots Are Driving Millions To Download Character.AI

What AI Is The Best? Chatbot Arena Relies On Millions Of Human Votes

The rapid advancement and implementation of artifi cial intelligence (AI) technologies have signifi cant economic, societal, and ethical consequences for Africa. Efficient governance is crucial to optimizing AI’s advantages while minimizing its risks. This article offers policymakers essential governance issues, suggests strategic methodologies for the appropriate oversight of AI technologies, and presents a framework for AI governance and contextualizes these within the setting of Africa.



Good AI governance must be based on good values. One such value is AI transparency which is essential for AI governance, as it fosters trust, accountability, and fairness. Transparent AI systems allow stakeholders to understand and evaluate decision-making processes, identify and correct biases and assure ethical and legal compliance. The other value is AI truth. Truthful AI prevents misinformation and promotes critical thinking in public conversation, strengthening AI systems’ legitimacy and building social trust needed for widespread adoption and benefi cial integration of AI technology into daily life. The other values are safety and security which are vital for AI systems, as AI interacts with people in different ways, building trust and adoption.



Prioritizing safety reduces accidents and errors in AI-driven industries, safeguarding lives, and money. The other value is ethics. Ethical design and deployment of AI technologies benefit society and minimize harm, including promoting justice, transparency, accountability, and human rights. The other AI value is privacy. Privacy is crucial for AI systems to secure personal data and retain trust in technology. By using strict privacy rules, AI systems protect personal data from unlawful access and exploitation.The AI governance framework proposed in this article entails human behavior, mechanisms for incentives and disincentives, institutional governance structures, policies and regulations, standards, and the law. AI governance involves adhering to AI values, using behavioral science to cultivate a culture that maximizes AI’s potential while minimizing associated risks, and implementing mechanisms to foster a culture that maximizes the potential benefi ts while limiting its associated risks. 



Establishing an institutional structure combining the best practices derived from the Intergovernmental Panel on Climate Change (IPCC) and the International Atomic Energy Agency (IAEA) is recommended to regulate AI effectively. This entity would set global AI standards, monitor compliance, foster international cooperation, address ethical guidelines, establish safety protocols, provide a platform for sharing best practices and promote transparency.Establishing policies and regulations to control AI involves crafting legal frameworks that ensure ethical AI use, focusing on transparency, accountability, and fairness while protecting privacy and preventing discrimination. Key measures could include mandatory AI audits and strict data protection requirements. 



Governments might also create dedicated bodies to oversee AI practices and enforce these regulations, ensuring AI benefi ts society and adheres to ethical standards.Establishing AI standards involves creating uniform guidelines for AI design, development, and deployment, focusing on technical quality, ethical considerations, and compatibility. These standards should cover data privacy, algorithmic transparency, security, and bias prevention. Lawmakers should collaborate with experts and the public to craft adaptable, informed regulations.



This model proposed above governs the following aspects of AI: data, algorithms, computing, and AI applications. Data governance ensures ethical, accurate, and secure use of AI systems, while algorithmic governance ensures ethical behavior and impartial results. Computing governance ensures safe, responsible, ethical, and sustainable AI technology, as computer technologies permeate every part of life. Well-defi ned governance frameworks build public trust, promote more egalitarian technology access, and incentivize good uses of AI. This governance should include specifi c regulations for AI applications in critical sectors like healthcare and fi nance.



AI governance in Africa is crucial to prevent AI from exacerbating existing inequalities that divide the Global South from the Global North and creating new ones. There is a need for robust governance frameworks to ensure that AI systems are used responsibly, minimizing risks, and empowering Africans to benefi t from AI’s potential especially given the fact that much of the AI technology is developed in the Global North. 



Issues such as the potential for AI to displace workers in key sectors in Africa, such as manufacturing and routine service industries, must be dealt with carefully, as AI might eliminate any hope of Africa industrializing. There is also a need to mitigate the negative infl uence of AI on political processes, such as deepfakes and misinformation campaigns. 



African nations must develop national AI strategies, establish independent regulatory bodies, invest in AI education and capacity-building programs, and play an active role in shaping global AI governance discussions through mechanisms such as the African Union and the United Nations. In conclusion, AI governance frameworks must be dynamic and adaptable to technological advancements. Policymakers should collaborate with technologists, businesses, academia, and civil society to create comprehensive governance strategies that ensure AI serves the public good.

AI, Machine learning, robot hand ai artificial intelligence assistance human touching on big data network connection background, Science artificial intelligence technology, innovation and futuristic.

Expert-Speak: An Effective Framework For Governance Of AI In Africa

Artificial intelligence (AI) has made significant strides in all areas of our lives. AI can now monitor patients, safeguard buildings, improve manufacturing processes and write poetry. These are good uses of AI. There are, however, bad uses and characteristics of AI.



For example, AI can discriminate against digital minorities such as people of African descent or ethnic minorities. It can be weaponized with devastating consequences for peace and security. Given that AI is both good and bad, what should be done? We must ensure that AI is used to maximize the good and minimize bad uses. Various strategies have been deployed to maximize the good uses of AI. Furthermore, multiple techniques have been deployed to reduce the bad uses of AI. For example, ensuring that data for training AI systems is representative can minimize algorithmic bias and discrimination.



However, fixing defective algorithms is much easier than improving a flawed human being who intends to use AI negatively. For example, it is far more challenging to change a human being that discriminates against ethnic minorities than to fix an AI machine that discriminates against ethnic minorities. To improve the AI machine, we must apply the best practices of handling data, designing algorithms, and using AI technology, which requires good human behavior.



In AI, discussions of its development, deployment and regulation frequently focus on technological and ethical concerns. However, this discussion’s significant and underexplored aspect parallels human behavior and AI governance. These two generate a complex confluence that considerably impacts how AI technologies are conceived and deployed and how they are regulated. As AI permeates every aspect of our lives, understanding and leveraging this confluence of AI and human behavior is advantageous and is also required for developing AI systems that are both effective and fair. 



Humans are at the heart of AI development, and their decisions, prejudices, and actions affect AI systems.Behavioral science, which studies human behavior   via    psychological, cognitive, and emotional lenses, provides essential insights into how developers and designers should approach the building of AI. It highlights the cognitive biases that can influence algorithm design and the ethical blind spots resulting from prioritizing technical efficiency over social consequences.



Incorporating human behavior into AI governance requires identifying and addressing these human issues. It entails developing frameworks enabling developers to reflect on the potential biases they bring to the design process and cultivating a culture that values ethical considerations and societal wellbeing over technical innovation.



End-user behavior must also be considered when governing AI. Behavioral science provides a lens through which to investigate how people engage with AI systems, such as responding to recommendations, making decisions based on AI-generated data, and building trust in AI technologies. These findings are critical for developing AI systems that are not only user- friendly but also promote beneficial behavioral outcomes, such as improving decision-making processes and preventing the reinforcement of negative biases.



Furthermore, behavioral science can inform public education campaigns on AI, enabling users to be more critical and educated in their interactions with AI systems. Governance frameworks based on behavioral science can raise an understanding of AI’s possible biases and limits, allowing people to interact ethically and effectively with AI.



The link between human behavior and AI governance is dynamic. As AI technologies advance, so will the societal norms and behaviors that shape and are shaped by them. Governance frameworks must be adaptive and ready to respond to new insights from behavioral science into human-AI interaction and the societal repercussions of AI breakthroughs.



This adaptability necessitates a participatory and inclusive governance strategy involving AI developers, users, behavioral scientists, ethicists, policy-makers, and other stakeholders in ongoing discourse. This strategy can help to keep governance frameworks current and thriving in the face of rapid technological development and shifting human behaviors.



Education is critical to guaranteeing the ethical governance of AI since it provides developers and consumers with the knowledge and skills needed to navigate the complicated moral environment of AI technology. Technologists can gain a thorough awareness of the ethical consequences of their work by participating in comprehensive educational programs that integrate ethics, data privacy, and societal effects into the core curriculum of computer science and AI courses. 



Education can help people understand AI technologies, promoting informed and critical engagement with AI systems. By incorporating ethical considerations into all stakeholders’ education in creating and using AI, we can foster a culture of responsibility and accountability. This strategy teaches individuals to foresee and address ethical difficulties and promotes the advancement of AI systems that emphasize human values and social wellbeing. As we set the road for the future of AI, let us not underestimate the value of understanding human behavior in guiding us toward more responsible and beneficial AI governance

AI (Artificial Intelligence) concept. Electronic circuit. Communication network.

The Dynamic Link Between Human Behavior And AI Governance

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



Apple’s new line of&nbsp;<a href="https://www.apple.com/apple-events/" rel="noreferrer noopener" target="_blank">iPad Pros</a>&nbsp;will include a processor the company claims is an “outrageously powerful chip for AI,” as the tech giant laid the groundwork for long-anticipated generative AI features across its products amid&nbsp;<a href="https://www.washingtonpost.com/technology/2024/05/02/apple-sales-ai-iphone-earnings-regulations/" rel="noreferrer noopener" target="_blank">investor concern</a>&nbsp;that it’s falling behind in the race to harness the new technology.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



The new M4 chip represents an upgrade over the M2 chips that powered the last generation of iPads and the M3 chips that power Apple’s current generation of MacBook laptops, the company said in an&nbsp;<a href="https://www.apple.com/apple-events/" rel="noreferrer noopener" target="_blank">announcement</a>&nbsp;Tuesday.



Tuesday’s announcement didn’t offer specifics about potential AI features that could be built into Apple tech, though Tim Millet, Apple’s vice president of platform architecture, gave one example, claiming that users would be able isolate the subject of a 4K video and remove the background with just a tap in Apple’s Final Cut Pro app.



Millet said the neural engine powering the AI capabilities in the M4 chip has been included in Apple chips for years, but this latest neural engine is 60 times more powerful than Apple’s earliest models and “more powerful than any neural processing unit in any AI PC today.”



On Tuesday, Apple announced a new line of&nbsp;<a href="https://www.apple.com/ipad-pro/" rel="noreferrer noopener" target="_blank">iPad Pros</a>&nbsp;that the tech giant called its thinnest yet, coming in 11-inch and 13-inch models with OLED screen technology starting at $999 for the 11-inch model.



It also announced its new&nbsp;<a href="https://www.apple.com/ipad-air/" rel="noreferrer noopener" target="_blank">iPad Air</a>, running on the M2 chip,which comes in a new, larger 13-inch option for $799—both the iPad Air and the iPad pro are available to order online Tuesday and in stores May 15.



Apple&nbsp;<a href="https://finance.yahoo.com/quote/AAPL?.tsrc=fin-srch" rel="noreferrer noopener" target="_blank">stock</a>&nbsp;was slightly up—less than a percentage point—following Tuesday’s announcement.



<h2 class="wp-block-heading" id="h-what-to-watch-for">WHAT TO WATCH FOR</h2>



Apple could unveil more of its plans for AI at its upcoming&nbsp;<a href="https://www.apple.com/newsroom/2024/03/apples-worldwide-developers-conference-returns-june-10-2024/" rel="noreferrer noopener" target="_blank">Worldwide Developers Conference</a>&nbsp;on June 10. CEO Tim Cook said Tuesday the company intends to “talk about the future of our platforms and share some exciting details about what’s to come” at the event. Cook has&nbsp;<a href="https://www.cnbc.com/2024/02/28/apple-annual-shareholder-meeting-2024-ai-investments.html" rel="noreferrer noopener" target="_blank">previously said</a>&nbsp;the company is “investing significantly” in AI and would have more announcements on the subject “later this year.”



<h2 class="wp-block-heading" id="h-contra">CONTRA</h2>



Apple’s plans for artificial intelligence could face immediate competition. The Verge reports Microsoft is&nbsp;<a href="https://www.theverge.com/2024/4/8/24116587/microsoft-macbook-air-surface-arm-qualcomm-snapdragon-x-elite" rel="noreferrer noopener" target="_blank">set to host</a>&nbsp;an event in Seattle this month where it plans to unveil its vision for the future of “AI PCs” and could launch new hardware featuring its Arm AI chips.



<h2 class="wp-block-heading" id="h-key-background">KEY BACKGROUND</h2>



Sales of Apple’s flagship iPhone have been slumping, down 10% year-over-year in the first three months of 2024, driving a 4% decrease in revenue last quarter. And while Apple is considered the most profitable American public company, its stock has been&nbsp;<a href="https://www.forbes.com/sites/dereksaul/2024/05/02/apple-earnings-come-in-hot-as-china-blow-less-painful-than-feared/?sh=5f71ff956903">trending downward</a>&nbsp;of late due to lower iPhone demand in China and concern over Apple’s lack of major plays in the field of artificial intelligence.



<h2 class="wp-block-heading" id="h-big-number">BIG NUMBER</h2>



38 trillion. That’s how many operations the new M4 chip’s neural engine can perform per second, Apple claimed on Tuesday.<a href="https://www.forbes.com/sites/jamesfarrell/"></a>

American multinational technology company Apple store seen

Apple Promises AI Features In New IPad Pro Chips—As AI Tech Race Heats Up

It’s an auditory crisis. The perfect mimicry of the human voice by artificial intelligence (AI) used by criminals to access organizations, discredit governments and leaders, steal data and money, and exploit people and companies. A woman was tricked into thinking her daughter had been kidnapped – the terrified voice on the end of the call was an AI fake. An employee in a multinational enterprise was conned into paying cybercriminals $25 million because he believed he was talking to the company’s Chief Financial Officer and Tom Hanks’ voice was cloned to sell dental plans.



If a fraudster can mimic someone’s voice, they can bypass security checks designed to use voice biometrics. They can fool people into believing that they’re talking to a trusted friend and colleague. They can slide past security barriers and connect with people because their fakes are so good, nobody can tell the difference.



“It’s the trust factor,” explains Adrianus Warmenhoven, cybersecurity expert at NordVPN. “As humans we have implicit trust anchors – I can read your body language when I see you, I can hear inflections and reactions in your voice on the phone and these anchor trust between us. These were developed by being in school, going to work, seeing people. Now they’re being used by criminals to make connections and successful scams.”



Voice is easy to start with. It can be trained easily and there are plenty of applications online. Anyone can download an AI and clone someone’s voice. The technology capable of converting voice to text, text to voice and then applying it to anything from fake bank calls through to scams designed to phish passwords or con family members is readily available.



“How accurately can you pick up someone’s voice? Are the slight tonal differences not just background noise? What if they’ve told you they’re not feeling well? The last two are the highest contributors, accounting for more than 80% of the threats we are seeing in terms of how voice recognition can be compromised,” says Vukosi Sambo, Executive – Head of Data Insights and AIat AfroCentric. 



“We are also seeing instances where someone records a person’s voice and then uses it to authenticate themselves as that person to gain access to information or systems.” 



Getting hold of a person’s voice isn’t difficult either. Cybercriminals simply turn to the one thing they’ve used to hone their craft for years – social media. As Ryan Mer, CEO of eftsure Africa, points out: “People post videos on social media, they share voice notes on WhatsApp, and in the business space, key people have some form of media, whether it’s an interview on TV, radio or a podcast.”



The technology is capable of generating a legitimate voice profile using only a few seconds of these videos and voice snippets. Then, that voice can be used to get in touch with people in the business, especially the finance team, to swindle them out of sensitive information or get them to perform certain tasks. It’s not always a case of getting someone to transfer millions, it can also be trying to access the system for data that can be sold for millions, or to infiltrate a business to commit long-term fraud from within.



Anyone can go onto the dark web and, for a small fee, ask for a deep fake video saying whatever they want. Nobody is going to ask how this will be used. Nobody will care about the repercussions of its use. It is also very likely the next creator of millionaires and billionaires who have used AI to achieve their financial goals, as nefarious as those may be.



Sambo adds: “It’s important to understand what the organization is entitled to in terms of collecting and storing voice data. If you’re not careful, you could infringe individual rights in light of the AI threat. Can companies that record calls for quality and security purposes really protect themselves from this perspective?”



“Considering how this technology is available to anybody these days for next to nothing, security has to take a multi- layered approach,” says Lance Fanaroff, co-founder of iiDENTIFii. “You need to manage access control based on who has access to what; focus on individual access tools such as two-factor authentication and biometrics; and then invest into technologies designed to identify and mitigate potential threats on a granular, individual, level.”



There is a positive side to the conversation – the technologies designed to tackle the threats are evolving just as rapidly. They’re more resilient and alert, capable of adapting to the potential deep fake risks with agility. However, there is only so much a company can do to protect its people and its systems. As Kabelo Makwane, Managing Executive: Cloud, Hosting &amp; Security at Vodacom Business Africa, concludes: “What has become important now is finding the right balance between leveraging the technology, not locking down systems, and still finding a way of layering security so there remains space for growth and productivity.”

Asian woman using smartphone surrounded by beams of light. Metaverse and Artificial Intelligence

AI Has Stolen Your Voice… And Why It’s An Auditory Crisis

Five years ago, I couldn’t imagine asking boards and business leaders whether robots would one day run their companies.



However, the massive increase in awareness of the potential of large language models is forcing executives to explore how to use robots and artificial intelligence in day-to-day decision-making.



In fact, the rise of executive robots has already started.



For example, in May 2023, Forbes reported that Dictador, a progressive premium brand rum distiller, had appointed an AI CEO called Mika.



It is gimmicky for sure, as humans are still very much controlling her AI strings, but as Mika reportedly said in an interview with Reuters, “My decision-making process relies on extensive data analysis and aligning with the company’s strategic objectives.” She went on to explain how she was devoid of personal bias, which helps ensure that strategic choices are prioritized in line with the organization’s best interests, not hers.



This sounds amazing. So, is Mika the forerunner of the mass adoption of AI for corporate governance and leadership roles?



For once, the likely answer is yes, absolutely.



For starters, the demand for a solution like this is apparent.



Humans regularly make bad decisions, and more often than not, this leads to someone losing a lot of money.



Why, for example, did OpenAI’s board sack Sam Altmann (before he returned as CEO in November last year)?



What led Elon Musk to rebrand Twitter to X?



And why didn’t Silicon Valley Bank diversify its risk away from startups?



Decisions like these wipe out trillions of dollars of value every single year. And these three examples are just the tip of the iceberg.



Further, those impacted aren’t just the super-wealthy. Often, it’s the poorest who see their life savings and pensions hit hardest.



All of which means there is a huge interest from everyone, from governments to investors, to find ways to improve decision- making and corporate governance.



We already spend billions of dollars for consultants and business schools to develop leaders and models to help companies maximize profits while minimizing risks.



But these billions will quickly switch to AI alternatives if there is even the smallest of probabilities that technology will help improve a stock’s potential returns.



So, the demand is there.



But how long will we have to wait for the likes of the already hugely-impressive ChatGPT to offer intelligence that can not only answer questions in narrow fields but actually analyze data from multiple sources, draw inferences, consider interdependencies, develop execution plans, draw up funding requirements, consider resource allocations, raise funding and build support along with all the other tasks and activities that are required in any modern-day business?



Mustafa Suleyman, founder of DeepMind and Inflection.AI, explores this question in his recent bestseller, The Coming Wave.



Specifically, he asks how long it will be before machines answer and act on prompts such as “Please design and execute a strategy that will allow me to make $1mill on Amazon in as few months as possible with just $100K of investment.”



His conclusion? “Aside from the legal requirements of registering as a business on the marketplace and getting a bank account, all of this seems to me eminently doable. I think it will be done within the next year and probably fully autonomously within three to five.”



When an industry insider as respected as Suleyman makes a comment like this, we should sit up and listen.



And it makes absolute sense when you consider that a potent combination of factors is driving development in AI. Breakthroughs in machine learning algorithms, dramatic increases in computing power, the abundance of extensive data sets, advancements in cloud computing, enhanced global connectivity, escalating demand across industries and the democratization of access through open-source initiatives are just some of the factors propelling it at exponential rates.



And, of course, the biggest factor of all is perhaps the simple fact that we are now using AI to build AI, as more and more code is being written by machines, not developers. So perhaps the real question isn’t whether or even when robots will run companies. Shareholders and boards might do better considering what types of leaders they need to employ to manage the transition from human to augmented to algorithmic leadership. This is not an easy question to answer. There is no template for designing leadership systems for robots. Perhaps ChatGPT has the answer?

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Expert-Speak: Will Robots Run Companies?

As language models like ChatGPT and Gemini have ushered in a new age of AI in Silicon Valley, the world’s most powerful tech companies are looking ahead to drug discovery and digital biology.



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As Nvidia CEO Jensen Huang scanned the audience at the JPMorgan Healthcare Conference this January in San Francisco, the biggest health tech event of the year, he acknowledged that he was on unusual ground.



“You’re not my normal crowd,” he said to the room of health and biology technologists, during a fireside chat with Recursion, a drug discovery firm that Nvidia pumped $50 million into last year.



The audience may not have been part of his core demographic, but he&#8217;s hoping that will change. Over and over again, Huang has touted digital biology as the “next amazing revolution” in technology. As the AI boom has swept Silicon Valley, Nvidia has built a more than $60 billion a year business and last summer became one of the few companies with a market cap in the trillions. In health and biotech, it sees more opportunities to fuel its growth.



“It&#8217;s been declared we are the next many-billion dollar business for Nvidia,” Kimberly Powell, Nvidia’s vice president of healthcare, told&nbsp;Forbes. She said the company aims to provide chips, cloud infrastructure and other tools to more biotech firms.



Now that large language models like OpenAI’s ChatGPT and Google DeepMind’s Gemini have mainstreamed generative AI, several of the world’s most powerful tech companies are looking to biotech as the next frontier in artificial intelligence — a frontier where AI isn’t generating funny poems from a prompt, but rather the next life-saving drug.



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“It&#8217;s been declared we are the next many-billion dollar business for Nvidia.”Kimberly Powell, Nvidia’s vice president of healthcare
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At Nvidia, arguably a backbone of the AI revolution because of its powerful GPU chips, the bulk of investments at the company’s venture capital arm over the past two years have been in drug discovery. At DeepMind, the Google AI lab’s AlphaFold model — a groundbreaking tool for predicting protein structures — has been used by academic researchers over the past year to develop a &#8220;molecular&#8221; syringe to inject medicine directly into cells, and to research crops that are less dependent on pesticides. The interest in biotech is industry-wide: Microsoft, Amazon and even Salesforce have protein design projects as well.



While using AI in drug discovery is not exactly a new trend — DeepMind first unveiled AlphaFold in 2018 — executives at both DeepMind and Nvidia told&nbsp;Forbes&nbsp;that this is a breakthrough moment, thanks to a confluence of three things: the mass of training data now available, the explosion of computing resources and advancements in AI algorithms. “The three ingredients are here for the very first time,” Powell said. “This was not possible five years ago.”



AI has great potential in the biotech space because of its sheer complexity — just take the problem that AlphaFold targets. Proteins are the basic machinery of your body, managing a wide variety of functions. All of these functions are reliant on the three dimensional shape of a protein. Every protein is made up of a sequence of amino acids, and interactions between those amino acids and the external environment determine how the protein “folds” — which dictates its ultimate shape. Being able to predict the shape of a protein based on its amino acid sequences is of intense interest to biotech companies, which can use those insights to design everything from new drugs to improved crops to biodegradable plastics.



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“It was always this kind of lunatic, fringe thing. Very much out of the mainstream.”David Baker, director of the Institute for Protein Design at the University of Washington
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This is where deep learning comes in: training AI models on hundreds of millions of different protein sequences and their underlying structures help those models uncover patterns in biology without necessarily needing to do the expensive computations required by a true molecular dynamics simulation. Fully simulating proteins requires such intense computational resources that institutions have designed and built supercomputers specifically to handle this type of problem, such as the Anton 2 at the Pittsburgh Supercomputing Center.



The boom in drug discovery tech isn’t only coming from the AI tech giants. Since 2021, there have been 281 venture capital deals worldwide in AI drug discovery startups, accounting for $7.7 billion in investment, according to Pitchbook. The biggest spike occurred in 2021 as the pandemic took hold, when 105 deals were made, up from 65 the year before, tapering to 67 deals in 2023. In a&nbsp;<a href="https://pitchbook.com/news/reports/q4-2023-biopharma-report" rel="noreferrer noopener" target="_blank">report</a>&nbsp;published earlier this month, the analyst firm noted that there’s still a strong level of enthusiasm “for early-stage firms integrating AI into drug discovery and development.” The rise of generative AI has also sparked increased interest, said David Baker, director of the Institute for Protein Design at the University of Washington.



“It was always this kind of lunatic, fringe thing. Very much out of the mainstream,” said Baker. Now, he said, “everyone is talking about it.” Since the Institute of Protein Design’s founding in 2012, more than 20 startups have been spun out of the program, said Baker. Ten of them — including Archon Biosciences, which develops nanomaterials for regenerative medicine and cancer, and Lila, creating treatments for fibrotic diseases — have come in recent years, since 2021.



At DeepMind, it wasn&#8217;t until the Covid-19 pandemic hit that researchers truly understood the stakes of their research. They&#8217;d worked for almost 5 years to develop AlphaFold, and as they were retraining the model for its second generation, the entire world began sheltering in place because of a mysterious virus. “That really brought home the importance of the problem,” Pushmeet Kohli, vice president of science for DeepMind, told&nbsp;Forbes.



The result of DeepMind’s retraining was AlphaFold 2, a groundbreaking model that could so accurately predict protein structures that organizers at CASP, a worldwide research contest for protein folding, emailed DeepMind to ask if the company somehow cheated, Kohli recalled, laughing.



The effort has been so promising that cofounder Demis Hassabis spun out a separate company at Alphabet based on AlphaFold’s breakthroughs in 2021. Called Isomorphic Labs, the startup focuses on drug discovery and is helmed by Hassabis himself. Just this year, for example, Isomorphic Labs inked research deals with&nbsp;<a href="https://storage.googleapis.com/isomorphiclabs-website-public-artifacts/ISOMORPHIC_LABS_LILLY_07_01_24.pdf" rel="noreferrer noopener" target="_blank">Lilly</a>&nbsp;and&nbsp;<a href="https://storage.googleapis.com/isomorphiclabs-website-public-artifacts/ISOMORPHIC_LABS_NOVARTIS_07_01_24.pdf" rel="noreferrer noopener" target="_blank">Novartis</a>&nbsp;collectively worth up to nearly $3 billion if all the milestones are met — and that doesn’t count lucrative royalties from potential drug sales that result from these partnerships.



In 2022, Nvidia unveiled BioNeMo, a generative AI platform that helps developers accelerate the training, deployment and scaling of large language models for drug discovery. At&nbsp;<a href="https://www.forbes.com/sites/richardnieva/2024/02/15/nvidia-nventures-ai-investments/?sh=561e51446025">Nventures, the chip maker’s venture capital arm</a>, seven of the unit’s 19 overall deals have been in AI drug discovery startups, including Genesis Therapeutics, Terray and Generate Biomedicines — the largest of any investment category.



“The computer-aided design industry created the first $2 trillion chip company,” Powell said, referring to Nvidia and its stratospheric rise over the past year. “Why wouldn&#8217;t the same computer-aided&nbsp;drug discovery&nbsp;industry build the next trillion dollar drug company?” She added, “Which is why we are investing in the way that we are.”



Several other tech giants have their own protein folding efforts. Last year, Salesforce debuted ProGen, a protein-generating AI model, and Microsoft released EvoDiff, a similar, but open source model. Amazon also released protein folding tools for SageMaker, its AWS machine learning platform. Even ByteDance, TikTok’s parent company, appears to be recruiting for science and drug design teams,&nbsp;Forbes&nbsp;<a href="https://www.forbes.com/sites/alexandralevine/2024/01/02/tiktok-bytedance-pharmaceuticals-drug-discovery-science-biology-chemistry-ai-china/?sh=3b8b0b250874">reported</a>&nbsp;in January.



Still, as promising and hyped as AI drug discovery is, there are setbacks. It still takes years to get drugs through clinical trials, and while the FDA so far has okayed clinical trials for&nbsp;<a href="https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-drug-development" rel="noreferrer noopener" target="_blank">over 100 new drug candidates</a>&nbsp;that use AI or machine learning for development, it it will likely be years before any hit the market.



In some cases, the difficulties associated with drug discovery has caused big tech companies to abandon that research. Last August, Facebook parent Meta shuttered its protein folding team. The researchers at the unit later struck out on their own, founding a company called EvolutionaryScale,&nbsp;Forbes&nbsp;<a href="https://www.forbes.com/sites/kenrickcai/2023/08/25/evolutionaryscale-ai-biotech-startup-meta-researchers-funding/?sh=191e6c7e140c">reported last year</a>. Meta declined to comment on the reason for shutting down the project.



One important bottleneck that tech companies will need to focus on is having enough training data. Newer foundational models like GPT are reliant on reinforcement learning, a method where algorithms can process unlabeled information through trial and error. That makes them even more reliant on high-quality data, Anna Marie Wagner, head of AI for synthetic biology company Ginkgo Bioworks told&nbsp;Forbes. Last summer, her company&nbsp;<a href="https://investors.ginkgobioworks.com/news/news-details/2023/Ginkgo-Bioworks-and-Google-Cloud-Partner-to-Build-Next-Generation-AI-Platform-for-Biological-Engineering-and-Biosecurity/default.aspx" rel="noreferrer noopener" target="_blank">entered into</a>&nbsp;a five-year strategic partnership with Google Cloud to pair its AI expertise with Ginkgo’s ability to quickly generate biological data in its automated labs, which can then be immediately put back into the AI model as new training data. This combination, she said, helps to better optimize the discovery process.



Additionally, she said, Ginkgo has the ability to validate model predictions quickly. Counterintuitively, that makes the quirk of AI models sometimes hallucinating — producing wrong or misleading results to a prompt — “a feature, not a bug” because it can lead to interesting discoveries that might have been unimaginable to scientists. “We want the model to come up with the crazy stuff, because that’s where we start seeing order of magnitude improvements.”



Kohli puts the data problem more bluntly: “Garbage in, garbage out.” Still, as the industry works to fix those issues, he has already seen the impact that AI has had on biological research. &#8220;When I go to conferences and see the change in how biologists were doing their work earlier, and how they&#8217;re doing their work today, that&#8217;s an amazing transformation,” he said.

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Why Nvidia, Google And Microsoft Are Betting Billions On Biotech’s AI Future

Artificial intelligence (AI) has emerged as a revolutionary tool, reshaping industries, streamlining processes, and improving decision-making. The success of AI is because we now have access to more data, and we possess adequate computational infrastructure to analyze such data. AI has enormous potential in the legal field, promising to transform how legal practitioners function and individuals access the justice system. 



However, this potential is not devoid of ethical concerns and obstacles.



The function of AI in the legal domain is diverse. AIdriven research tools can rapidly analyze extensive legal databases, furnishing attorneys with insights in a previously unattainable manner. It entails the utilization of chatbots and virtual assistants to provide individuals with legal guidance, thereby enhancing the accessibility of legal information. 



AI saves time and money when producing legal documents using document automation tools.



Predictive analytics can predict legal outcomes, enabling litigants and attorneys to make well-informed decisions. Online dispute resolution platforms provide a viable substitute for conventional litigation, enhancing the efficiency and accessibility of dispute resolution. Nevertheless, as AI gains prominence in law, we must exercise caution and remain vigilant regarding the obstacles to this revolutionary technology.



The first such obstacle is the fairness and bias of AI systems, which are potential sources of concern. Algorithms for machine learning are trained using historical data, which may contain societal biases. AI could perpetuate and even exacerbate preexisting discrimination in the legal system if these prejudices are not addressed. AI development must prioritize fairness and equity, necessitating ongoing vigilance to identify and address bias in AI applications. Secondly, the opaqueness of AI decisionmaking processes raises concerns regarding transparency and accountability. In legal contexts, individuals have a right to be informed of the reasoning behind decisions made by AI systems.



Legal experts and technologists must collaborate to guarantee the transparency of AI systems and allow individuals to contest AI-generated outcomes. However, AI technology is lagging, and AI systems are subjected to the accuracy-transparency dilemma, whereby the more accurate the AI model, the less transparent it is, and vice versa. This is because the high accuracy of the AI model correlates to the increased complexity of the model. Furthermore, the more complex the AI model, the more accurate it is, but this results in reduced transparency of the model.



Thirdly, there is the problem of the security and privacy of individuals. Legal issues frequently necessitate the use of confidential personal data. Implementing robust data protection measures to secure individuals’ rights and privacy is critical.



Legal professionals must thoroughly contemplate the ethical and legal ramifications and enforce rigorous data security protocols when dealing with personal data. This requires technology, which is not necessarily available in many African countries. The African Union (AU) must ensure that groups of countries jointly procure such technologies to reduce the burden of the cost of this technology.



Furthermore, we must train enough people to deploy such technologies. Fourth, as AI’s capacity for legal research and document automation expands, concerns may arise regarding the potential displacement of legal professionals. However, rather than replacing legal professionals, AI should be considered a supplement to their work. By utilizing AI, legal professionals can increase productivity, decrease expenses, and improve their capacity to render expert opinions.



Fifth, legislative bodies and governments must establish transparent regulatory frameworks for AI. These regulations must delineate principles of ethics, foster transparency mandates, and stipulate the responsibility of these AI systems. Achieving an optimal equilibrium between fostering innovation and safeguarding the rights of individuals is a highly challenging endeavor and requires the training of regulators and lawmakers to understand these technologies. 



The AU can be a catalyst to ensure such knowledge is accessible across Africa.



Sixth, a potential benefit of AI in law is its capacity to improve the accessibility of justice. Tools propelled by AI can increase the accessibility of legal information for those who cannot afford legal representation.



Online dispute resolution has the potential to offer economically viable substitutes for conventional litigation. However, we must ensure that these technologies do not exacerbate but rectify existing disparities in access to justice.



AI is not a silver bullet that can solve all legal problems, nor is it the precursor that will end the legal profession as we know it. However, when utilized responsibly and ethically, AI is a tool that has the potential to enhance the agency of legal practitioners and facilitate improved access to justice.



The coexistence of AI and the law can produce a legal system that is more equitable, efficient, and accessible.

AI And The Law –Navigating The Future Together

Finance is a crucial change agent in society, government, and technology.



The introduction of artificial intelligence (AI) is fundamentally altering the financial world. AI is a form of technology that confers intelligence on machines. In my 2013 book, Economic Modeling Using Artificial Intelligence Methods, I demonstrated how



AI could forecast economic indicators, predict stock prices in stock exchanges, perform credit scoring in banks, and model complex financial instruments such as options, futures, and derivatives. In our 2017 book, Artificial Intelligence and Economic Theory, Evan Hurwitz and I demonstrate how AI affects how economists think about demand and supply, pricing, and behavioral economics. Utilizing AI’s capabilities, the financial sector is on the verge of massive disruptive changes that present new opportunities and risks. This article examines how AI affects economic systems, specifically the financial sector, markets, and the government.



Using machine learning, predictive analytics, and natural language processing, AI has the potential to revolutionize the way institutions operate. Additionally, AI opens up new avenues for customer service, risk management, and business advice.



For example, AI-powered chatbots and virtual helpers help with customer service around the clock, simplifying user interfaces and making it easier to answer questions quickly.



Consequently, they enhance consumer experience and reduce expenses. For instance, in risk management and credit scoring, AI algorithms can examine enormous amounts of data to identify patterns and assess risk levels. This makes financial services available to a larger population.



In the investment world, robo-advisors have become popular. They use AI’s analytical capabilities to offer cheap, personalized financial advice. Through these changes, AI is making it easier for more people to use financial services and driving the global financial system to be more open to more people.



AI is also changing the way financial markets work. For example, AI has changed how stocks are bought and sold with high-frequency algorithmic trading. AI can analyze vast financial data in milliseconds to identify trends and make trades. This is a substantial improvement over traditional methods making markets move faster, more open and work better. However, increased market speed ushers market stability and systemic risks, requiring protection and strong oversight to avoid these problems.



Regulators worldwide seek to deal with AI’s problems, such as data protection and algorithmic transparency. Accordingly, there should be a balance between encouraging innovation and protecting the financial security and consumer interests in regulations. AI can simplify compliance procedures, monitor



financial transactions in real-time for illicit activities, and predict market glitches, making regulators more proactive.



In the African market, the African Continental Free Trade Area (AfCFTA), a trade deal that aims to increase trade significantly within Africa, offers unique opportunities for AI.



The agreement covers a broad range of aspects of Africa’s economy, such as digital trade and the protection of investments. Moreover, the number of countries in the AfCFTA will make it the largest free trade area globally, linking 1.3 billion people in 54 countries with a combined GDP of $3.4 trillion. AI can make the AfCFTA work better and reach its goals.



For example, AI can help improve trade logistics by making delivery systems, customs processes, and tracking and tracing more efficient. It can find the best ways to move goods, predict delays, and give traders real-time information. In addition, AI can analyze trade data to identify patterns, trends, and connections. This can help policymakers make better choices and predict and respond to future trends better.



AI-powered systems can make cross-border e-commerce more efficient, a sector expected to grow under the AfCFTA. AI can create personalized product recommendations and automate customer service. In education and training, AI can help people acquire the skills they need for an African economy that works better together.



However, for AI to achieve the goals of the AfCFTA, it is essential to have good AI governance and regulation. Furthermore, we need to invest in digital infrastructure and education.



In conclusion, AI is vital to changing how the world’s economic system works. It affects financial services, markets, and regulation. AI is ushering in a new age of innovation and efficiency.



However, as AI continues to change how the financial world works, a cautious and thorough approach is needed to make the most of its prospects and manage its risks well. There needs to be strong regulatory frameworks, investments in AI literacy and skills, and a commitment to ethical AI values. These objectives are essential if we want an AI-driven financial future that is both prosperous and sustainable in Africa.

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How Artificial Intelligence Affects The Financial Sector In Africa

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OpenAI—the company behind ChatGPT—is exploring ways for its popular generative artificial intelligence platform to be used in schools, according to <a href="https://www.reuters.com/technology/openai-explores-how-get-chatgpt-into-classrooms-2023-11-16/" target="_blank" rel="noreferrer noopener">Reuters</a>, marking a new undertaking for the company that’s been criticized by some educators for enabling cheating.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



Brad Lightcap, chief operating officer for OpenAI, said at a San Francisco conference last week that the company will likely create a team next year that will solely look into ways artificial intelligence can be used in education, Reuters reported.



Lightcap said at the conference that “most teachers are trying to figure out ways to incorporate (ChatGPT)” into how they teach, and that OpenAI is “trying to help them think through the problem.”



Artificial intelligence—and ChatGPT, specifically—have been criticized in the past for making it easier for students to cheat, even being&nbsp;<a href="https://www.forbes.com/sites/ariannajohnson/2023/01/18/chatgpt-in-schools-heres-where-its-banned-and-how-it-could-potentially-help-students/?sh=ffd34456e2c6">banned</a>&nbsp;by some schools and districts earlier this year.



<h2 class="wp-block-heading" id="h-big-number">BIG NUMBER</h2>



85%. That’s how many students—out of those who were able to compare human tutoring to using AI—said ChatGPT was more effective than working with a real person,&nbsp;<a href="https://www.govtech.com/education/k-12/is-chatgpt-better-than-a-human-tutor-survey-says-yes" target="_blank" rel="noreferrer noopener">according</a>&nbsp;to Government Technology.



<h2 class="wp-block-heading" id="h-key-background">KEY BACKGROUND</h2>



ChatGPT was released mid-school year last November, and districts nationwide almost immediately began banning the generative AI platform out of cheating concerns. Students are able to use generative AI platforms to write essays and complete homework, though it wasn’t hard to catch, <a href="https://www.nytimes.com/2023/06/30/technology/ai-chatbot-study-aid.html" target="_blank" rel="noreferrer noopener">according</a> to the New York Times, because of AI being in early stages and still “hallucinating,” or making things up. On Dec. 12, 2022, the nation’s second-largest district, Los Angeles Unified School District, became one of the first to block the site to “protect academic honesty,” though at the start of a new school year it introduced its own education-specific AI bot called “Ed” in about 100 schools, Politico <a href="https://www.politico.com/news/2023/08/23/chatgpt-ai-chatbots-in-classrooms-00111662" target="_blank" rel="noreferrer noopener">reported</a>. Other districts that banned it or limited access to the site <a href="https://www.forbes.com/sites/ariannajohnson/2023/01/18/chatgpt-in-schools-heres-where-its-banned-and-how-it-could-potentially-help-students/?sh=ffd34456e2c6">included</a> New York City Public Schools and schools in Montgomery County, Alabama. Since the release of ChatGPT, though, OpenAI has worked to show its value in education. In the fall, OpenAI and nonprofit Khan Academy <a href="https://openai.com/customer-stories/khan-academy" target="_blank" rel="noreferrer noopener">announced</a> a partnership to create an “AI-powered assistant” available to Khan students that works as “both a virtual tutor for students and a classroom assistant for teachers.”

In this photo illustration, the ChatGPT (OpenAI) logo is

OpenAI Exploring ChatGPT’s Potential In Classrooms—Despite Critics Saying AI Promotes Cheating, Report Says

Artificial intelligence (AI) is transforming companies and economies worldwide, including in Africa. Data is an essential component in the training of AI systems. Unfortunately, the lack of accurate, high-quality data is a significant impediment in Africa. Synthetic data, or data generated by a computer, may be used to train AI models. While synthetic data offers tremendous opportunities for African innovation and development, it poses significant risks that must be carefully assessed.



Gathering real-world data in many African regions is difficult, expensive, and time-consuming.



These obstacles are brought about by various factors, including social, cultural, technological, and infrastructural deficiencies. Understanding and managing varied cultural traditions and languages may be challenging, especially when gathering data from multiple locations and people. As a result, synthetic data provides a solution by enabling researchers and businesses to create massive databases tailored to their specific needs. 



Data poverty is a lack of access to high-quality data and the ability to use such data appropriately. It’s a significant issue that hinders economic progress, decision-making, and innovation and worsens poverty. The data availability and consumption discrepancy between Africa and the rest of the world reflects more profound disparities and has significant repercussions. 



As a result, critical innovations in health, education, and transportation operate better for the rest of the globe than for Africa. For example, due to Africa’s relative data scarcity, AI systems in Africa have fewer data sets to learn from than the rest of the globe.



Synthetic data is presented as a strategy to supplement this data scarcity. The generative adversarial networks (GANs) AI method is often used to create synthetic data. GANs consist of two neural networks (akin to an artificial brain), the generator and the discriminator. The generator produces new data, while the discriminator discriminates between real and fake data. 



After they are trained adversarially (i.e. generator producing synthetic data while the discriminator differentiating fake from real data), the generator and discriminator become as good as possible at their respective tasks. One benefit of using synthetic data is that personal or sensitive information is frequently eliminated, minimizing the risk of privacy violations. This is particularly important in businesses where data privacy is vital, such as healthcare. Furthermore, by making data more available, synthetic data may lower the barriers to entry for firms and inventors.



However, synthetic data has significant drawbacks. One of them is that the models used to generate synthetic data significantly influence its quality. It reflects limitations in data (such as bias and small size), resulting in compromised and less accurate AI models and potentially perpetuating inequality, injustice and poverty. This is not the intended consequence, so there is a need to develop ethical guidelines for using synthetic data. These should first guarantee that synthetic data is anonymized for privacy protection and does not include identifiable information that may be connected back to persons.



Second, synthetic data must adhere to data protection norms and regulations governing personal information use. Third, synthetic data should accurately replicate the underlying real-world data without inserting biases or distortions. One way to achieve this is to increase data size used to generate synthetic data. Fourth, synthetic data and the processes used to create it should be disclosed. 



Fifth, explicit procedures for generating, managing, and using synthetic data should be developed and publicized. Sixth, detect and prevent misuse, as well as monitor and audit the use of synthetic data regularly. Seventh, acquire informed consent from individuals whose data were utilized to produce synthetic data, if applicable. Eighth, clarify how synthetic data will be utilized and what privacy controls will be in place. Ninth, prevent biases in synthetic data from reinforcing stereotypes or discrimination.



Tenth, keep cultural norms and values in mind while developing and exploiting synthetic data, especially when it represents different populations. Eleventh, since GANs are used to generate synthetic data and are computationally costly, consider the environmental effect of data collection, storage, and production and seek to offset any negative impacts. Twelfth, establish specific processes for exchanging synthetic data with other institutions or researchers while meeting ethical standards. 



Thirteenth, collaborate with relevant stakeholders, such as ethics committees or review boards, to ensure that synthetic data activities are handled ethically. Synthetic data has the potential to be a game-changer in Africa’s AI journey, managing data scarcity, increasing privacy, and encouraging innovation. As Africa embraces AI and synthetic data, a balanced approach is essential. Policymakers, companies, and academics must work together to guarantee that synthetic data is used correctly and ethically.

Synthetic Data As A Double-Edged Sword In Africa’s AI Revolution

In its latest product launch, the unicorn AI startup is bringing bots that make it sound like you’re talking to well known people like Taylor Swift into your group chat



Inside Character.AI’s disheveled Palo Alto, California headquarters, employees at first appear to be hard at work, glued to their computer monitors. But rather than coding, many of them are engrossed in lively group chats with their colleagues and the AI chatbot characters that Character has become known for. Now, thanks to a new group chat function the startup launched Wednesday, they were chatting with work friends along with bots that anyone can build to create the illusion that you’re actually talking to the likes of Napoleon Bonaparte, Tony Stark or Lucifer.



“The feature was good enough that people stopped working sometimes to use it,” cofounder Daniel De Freitas told&nbsp;Forbes. De Freitas, the company’s president, has been particularly partial to gathering team members together to play Ship AI, a chatbot programmed to act like a text-based adventure game that lets group chat participants pretend to be astronauts exploring outer space.



The group chat feature is Character.AI’s latest move in cofounder and CEO Noam Shazeer’s bet that people will want to interact with a variety of different chatbot personas, rather than having a single, all-encompassing AI companion. By allowing the company’s subscribers, who pay $9.99 per month, to interact with each other and some of the startup’s 18 million AI bots in chats at the same time, Character is hoping to establish dominance as the go-to app for AI-powered entertainment while adding to its immediate revenue stream. Shazeer said that after “some period of time,” the company plans to make the feature free “because our goal is to empower everyone with AGI,” or artificial general intelligence.



Backed by nearly $200 million from VCs including Andreessen Horowitz, and valued at $1 billion in a March funding round, Character.AI has wowed the startup community with its engagement time — it claims registered users who send at least one message on a given day spend an average of two hours on the platform. Since its initial launch in September 2022, 20 million users have signed up for Character.AI, though traffic to its website has been declining since its May 2023 peak, per analytics provider SimilarWeb. Also in May, the startup began monetizing through its subscription service, which gives customers priority access to its platform (servers have often been overloaded, and non-paying users have to wait longer to get on) and early access to new features. Character.AI declined to share any statistics on its subscribers or its recent growth traction.



The group chat feature, which&nbsp;Forbes&nbsp;tested out, is still rudimentary. In the initial iteration of Character.AI’s group chat, human users are able to chat with one another as on any messaging platform. To invoke a bot’s response, however, a user must manually tap on the icon for the specific bot they want to speak, or a dice icon which selects one of the bots in the group chat to respond at random. The bots can respond to users’ questions, as well as to one other (though in the latter case, the human must still prompt the bot to respond).



In a group chat with three&nbsp;Forbes&nbsp;reporters and Character.AI’s most popular AI personas for singer Taylor Swift and NFL player Travis Kelce, a human user asked, “Tell us your deepest insecurities about dating Taylor” and tapped on the icon for Kelce’s bot.



“My biggest insecurity about dating @Taylor-Swift is that other guys will be jealous of me because they want to date her too. But I’m not afraid of the competition, she’s a great girl and I’m going to show her a great time. I won’t let her down,” the bot wrote.



After the Taylor Swift bot was prompted, it responded: “Haha, I love the confidence, Travis! Let’s meet up after the season, and I’ll let you show me a great time ;)”



There are other, more practical issues: the feature is only available on Character.AI’s mobile app, and the chatbots appeared to only respond to the most recent message from a human user.



The cofounders say product updates with better functionality are coming soon. The underlying AI is also about to improve dramatically, Shazeer told&nbsp;Forbes, because the company is beginning to receive fulfillment on an order of “many thousands” of Nvidia’s new line of H100 GPUs after a months-long delay due to supply chain shortages. The company plans to put the chips to use to train new large language models, he said.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
“AI is underhyped because the things that are going to be possible in the coming years are going to be really, really impressive compared to what’s possible now.”Naom Shazeer
</blockquote>



Part of the urgency to launch the product now, before a new model is ready, may have to do with several generative AI tools launched by Meta in late September. In an&nbsp;<a href="https://www.forbes.com/sites/kerryadolan/2023/09/26/mark-gets-meta-zuckerberg-talks-ai-and-that-musk-mma-fight-thats-never-going-to-happen/">exclusive interview</a>&nbsp;with&nbsp;Forbes&nbsp;last month, Mark Zuckerberg outlined a vision of bringing AI “characters” to his company’s various products. “You’ll be able to talk to them in WhatsApp and Messenger and Instagram, and they&#8217;ll be embodied as avatars in virtual reality,” he said. These include an AI assistant called “Meta AI” and 28 other characters that users can talk to in group chats. “That looks familiar,” Character.AI’s Twitter account&nbsp;<a href="https://twitter.com/character_ai/status/1707130316920635432/" target="_blank" rel="noreferrer noopener">quipped</a>&nbsp;after Meta’s announcement.



Shazeer said the group chat feature had been in the works for several months before Meta’s announcement, and he views Zuckerberg’s move into the space as something of a compliment. “It is great to see other companies getting inspired and building similar products — it’s a real testament to what we’re doing and to the engagement that we’re getting,” Shazeer said.



De Freitas and Shazeer, a coauthor on the seminal research paper on “transformers” that catalyzed the&nbsp;<a href="https://www.forbes.com/sites/alexkonrad/2023/02/02/inside-chatggpts-breakout-moment-and-the-race-for-the-future-of-ai/">generative AI boom</a>, met while working as AI engineers at Google, where together they developed an early large language model that would become the foundation for Bard. But in 2021, they left the company because they said they’d run into bureaucratic roadblocks implementing the technology into consumer-facing applications. Shazeer, a 20-year veteran who joined prior to Google’s IPO, said he departed despite a personal plea from CEO Sundar Pichai.



“He talked to me to see if he could encourage me to stay,” Shazeer told&nbsp;Forbes&nbsp;in a July interview. “But, basically I wanted to get this technology out to as many people as possible and just empower everyone with flexible AI. I think it was the right decision.” Shazeer said the company would have needed to release the chatbot they were working on to a wide audience for him to consider staying. “It just felt like Google was not going to be very comfortable launching something that could say anything, and that you really had to be a startup to launch something like that,” he said.



The pair founded Character.AI in November 2021, a year before public appetite for AI swelled when OpenAI released ChatGPT. Google unveiled Bard this past February. Still, Character.AI has continued to carve a niche for itself. The vast majority of the startup’s bots have been created by its user base, who can upload examples of what they want the character to say and give the model feedback to help it improve, Shazeer said in the interview this month.



Startup challengers Replika and Chai have emerged, but the space remained devoid of Big Tech challengers until Zuckerberg’s announcement last month. But Shazeer claims to be unfazed by these competitors. “We’re competing against the $2 trillion industry of legacy entertainment” — say, games, books and movies — “because people want a lot of the same things like fun, the social experience and interesting content. Those things are identical regardless of whether more companies are noticing our space,” he said.



Enter the group chat. Shazeer acknowledged that Character.AI has kinks to work out in the new feature to improve its usability, such as expanding its context window so that the AI can appear to remember longer durations of the conversation. “Right now the system is operating just based on a context window of a few thousand words, so characters are only reacting to whatever happened recently, which is highly suboptimal,” Shazeer said.



The bots also remain prone to “hallucinations” in which the AI outputs false information. After&nbsp;Forbes&nbsp;asked the startup’s flagship bot Character Assistant how it was trained, the bot stated it had access to, among other things, customer service calls and transaction data from banks like Chase, Wells Fargo and Bank of America. Shazeer and De Freitas said this was incorrect and the bot had made up the answer.



Up to now, Character.AI’s chatbots have been built on the same foundational model that it trained in summer 2022 using 1,000 Nvidia A100 GPU chips. After its full order is fulfilled, the startup will be able to train new AI models on 40 times the amount of computing power as its current model, Shazeer said. All the compute access is being rented from Google Cloud and other cloud providers for now; Shazeer said Character.AI is considering eventually building its own GPU cluster, but has made no firm decisions.



Character.AI is betting that the new models will bring its technology closer to AGI, expanding the range of use cases beyond entertainment. For Shazeer, this is one reason he claims to not be worried about declining traffic. “Really I think AI is underhyped because the things that are going to be possible in the coming years are going to be really, really impressive compared to what’s possible now,” he said.



That goes for Character.AI’s group chats too. In time, he said, the bots in the group chat will be able to respond to human messages automatically. In the future, a fictional AI character could “just step in and say something that will bring you together with somebody,” he said. “I think it’s going to be a magical moment when that happens.”



Rashi Shrivastava contributed reporting.

Character.AI’s $200 Million Bet That Chatbots Are The Future Of Entertainment

Production studios and fans alike are turning to generative AI tools to make voice actors say things they never said — and their jobs are on the line.



 oice actor Allegra Clark was scrolling through TikTok when she came across a video featuring Beidou, a swashbuckling ship captain from the video game&nbsp;Genshin Impact&nbsp;whom she’d voiced. But Beidou was participating in a sexually suggestive scene and said things that Clark had never recorded, even though the rugged voice sounded exactly like hers. The video’s creator had taken Clark’s voice and cloned it using a generative AI tool called ElevenLabs, and from there, they made her say whatever they wanted.



Clark, who has voiced more than 100 video game characters and dozens of commercials, said she interpreted the video as a joke, but was concerned her client might see it and think she had participated in it — which could be a violation of her contract, she said.



“Not only can this get us into a lot of trouble if people think we said [these things], but it’s also, frankly, very violating to hear yourself speak when it isn’t really you,” she wrote in an email to ElevenLabs that was reviewed by&nbsp;Forbes. She asked the startup to take down the uploaded audio clip and prevent future cloning of her voice, but the company said it hadn’t determined that the clip was made with its technology. It said it would only take immediate action if the clip was “hate speech or defamatory,” and stated it wasn’t responsible for any violation of copyright. The company never followed up or took any action.



“It sucks that we have no personal ownership of our voices. All we can do is kind of wag our finger at the situation,” Clark told&nbsp;Forbes.



In response to questions about Clark’s experience, ElevenLabs cofounder and CEO Mati Staniszewski told&nbsp;Forbes&nbsp;in an email that its users need the “explicit consent” of the person whose voice they are cloning if the content created could be “damaging or libelous.” Months after Clark’s experience, the company launched a “voice captcha” tool that requires people to record a randomly generated word and that voice must match the voice they are trying to clone.



The company, which is valued at about $100 million and backed by Andreessen Horowitz and Google DeepMind cofounder Mustafa Suleyman, is one of the hottest voice AI companies right now. Its technology only requires between 30 seconds to 10 minutes worth of audio to create what sounds like a near-identical replica of someone’s voice. Along with sites like FakeYou and Voice AI, which offer a free library of digital voices, it’s also at the center of generative AI’s impact on voice actors.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
“There’s no legal protection for voice like there is for your face or for your fingerprint.”Jennifer Roberts, voice actor
</blockquote>



Interviews with 10 voice actors revealed an already precarious industry on the brink of widespread change as employers begin to experiment with these text-to-speech tools. One voice actor&nbsp;Forbes&nbsp;spoke to said an employer told her she would not be hired to finish narrating a series of audiobooks the day after it announced a partnership with ElevenLabs, leading her to fear she would be replaced with AI. Another said her employer told her that they wanted to use ElevenLabs’ AI to speed up retake sessions, a standard part of recording audio that voice actors are paid for. When she told her employer she didn’t consent to her voice being uploaded to any AI site, the employer agreed, but she said she hasn&#8217;t been called in to do any retakes.



The community of voice actors first noticed an influx of AI generated voices after Apple Books launched&nbsp;<a href="https://authors.apple.com/support/4519-digital-narration-audiobooks" target="_blank" rel="noreferrer noopener">digital narration</a>&nbsp;of audiobooks with a suite of soprano and baritone voices in January 2023, said Tim Friedlander, the president of NAVA. Actors began discovering thousands of audio files of familiar voices being uploaded to various sites mostly by fans, he said. Most recently, famed actor Stephen Fry said that his voice was scraped from his narration of the Harry Potter books and cloned using AI. In a&nbsp;<a href="https://www.youtube.com/watch?v=zZfS8uk70Zc" target="_blank" rel="noreferrer noopener">talk</a>&nbsp;at CogX festival, Fry said the experience “shocked” him.



In a public&nbsp;<a href="https://docs.google.com/spreadsheets/u/1/d/1n6KZpcahyckjmzgsH90ghgNs5pcEQ57baavbjAI_ed8/edit#gid=0" target="_blank" rel="noreferrer noopener">spreadsheet</a>, hundreds of voice actors have requested to have their voices purged from AI voice generators Uberduck and FakeYou.ai, which have said they will take voices down from their sites if the voice’s owner reaches out. While FakeYou.ai still provides thousands of popular voices like those of John Cena and Kanye West that anyone can use, Uberduck removed user-contributed voices from its platform in&nbsp;<a href="https://www.uberduck.ai/post/new-voice-hosting-policy" target="_blank" rel="noreferrer noopener">July</a>. Uberduck and FakeYou.ai didn’t respond to multiple requests for comment.



One of the voice actors who has publicly requested his voice be removed from voice generators is Jim Cummings, the voice behind characters like Winnie-the-Pooh and Taz from Looney Tunes. He told&nbsp;Forbes&nbsp;he would only agree to users templating his voice if he and his family received royalties for it. “Keep your paws off my voice,” he said.



<hr class="wp-block-separator has-alpha-channel-opacity"/>



<h2 class="wp-block-heading" id="h-a-legal-dilemma">A Legal Dilemma</h2>



Like striking film actors, who are sounding the alarm about the coming of AI and how it could affect their jobs, voice actors are on the front lines of technological change. But unlike other creative fields, where&nbsp;<a href="https://www.forbes.com/sites/cyrusfarivar/2023/09/11/michael-chabon-other-literary-giants-sue-openai-over-alleged-copyright-infringement/?sh=4d2b431e66a4">authors</a>&nbsp;and&nbsp;<a href="https://www.theverge.com/2023/1/16/23557098/generative-ai-art-copyright-legal-lawsuit-stable-diffusion-midjourney-deviantart" target="_blank" rel="noreferrer noopener">artists</a>&nbsp;are banding together in class-action lawsuits to push back against their copyrighted work being used to train AI models, voice actors are uniquely vulnerable. Even though voices are inherently distinguishable, they aren’t protected as intellectual property. “There’s no legal protection for voice like there is for your face or for your fingerprint,” said Jennifer Roberts, the voice behind several video game characters. “Our hands are tied.”



A recording of a voice, however, can be copyrighted, and according to Jeanne Hamburg, an attorney for law firm Norris McLaughen, using a voice for commercial purposes can be protected by “rights of publicity,” which prevents celebrities&#8217; likenesses from being exploited. That’s in theory, though: Most contracts signed by voice actors don’t stop recordings of their voices from being used to train AI systems. For more than a decade, contracts have stated that producers “own the recording in perpetuity, throughout the known universe, in any technology currently existing or to be developed,&#8221; said Cissy Jones, a voice actor who is part of the founding team at National Association of Voice Actors (NAVA), a newly formed union for voice actors.



Those contracts were largely written and signed before the advent of AI systems. “Voice actors have not provided informed consent to the future use of an audio recording and haven&#8217;t been fairly compensated for it,” said Scott Mortman, an attorney for NAVA. “And so protections need to be strengthened significantly in the wake of AI.”



That’s why NAVA, and the actors union SAG-AFTRA, are working to strike verbiage from&nbsp;<a href="https://navavoices.org/synth-ai/" target="_blank" rel="noreferrer noopener">contracts</a>&nbsp;that allows employers to use an actor’s voice to create a “digital double,” or “synthesize” their voice through machine learning. The organizations have also developed new boilerplate language to add into contracts that would protect voice actors from losing the rights to their voices.



<hr class="wp-block-separator has-alpha-channel-opacity"/>



<h2 class="wp-block-heading" id="h-a-myriad-of-misuses">A Myriad of Misuses</h2>



Like Clark, numerous voice actors have experienced fans manipulating their voices using generative AI tools to create&nbsp;<a href="https://www.ign.com/articles/voice-actors-speak-out-on-nsfw-skyrim-mods-nexus-mods" target="_blank" rel="noreferrer noopener">pornographic</a>,&nbsp;<a href="https://www.vice.com/en/article/dy7mww/ai-voice-firm-4chan-celebrity-voices-emma-watson-joe-rogan-elevenlabs" target="_blank" rel="noreferrer noopener">racist and violent</a>&nbsp;content. Even when fans use AI voices to create innocuous memes or other kinds of fan content, voice actors have spoken up on social media,&nbsp;<a href="https://www.themarysue.com/voice-actors-dont-want-you-using-ai-to-copy-their-voices/" target="_blank" rel="noreferrer noopener">forbidding</a>&nbsp;people from fabricating their voices.



NAVA member Jones, whose voice has been featured in Disney shows and Netflix documentaries, found TikTok videos in which fans had used Uberduck to create clones of her voice saying inappropriate things. “Not only is my voice saying something I would never say, that stuff is out there in the world,” Jones told&nbsp;Forbes. “If potential buyers hear our voices saying that, how will that affect my future work?” After she reached out, Uberduck removed her voice from the platform, Jones said.



AI generated voices have also become a new medium for harassment. Abbey Veffer, whose voice has been featured in games like&nbsp;Genshin Impact&nbsp;and&nbsp;The Elder Scrolls, said she was doxed by someone who had created a clone of her voice in February. The person created a Twitter account with her address as the username, generated an AI clone of Veffer’s voice and then made the clone say racist and violent things. The anonymous user directly messaged the recording to Veffer and pinned it at the top of the Twitter account. They claimed to have used ElevenLabs’ technology. The experience, Veffer told&nbsp;Forbes, was “intense” and “very upsetting.”.



But when Veffer reached out to ElevenLabs with her concerns, the company said that the clone was not created using its software and was part of an “organized smear campaign” against the startup, according to messages reviewed by&nbsp;Forbes.&nbsp;Three days after Veffer reached out to Twitter, the account was suspended and the video was taken down but her residential address remained on the site for three months, she said.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
“Controlling how our voice gets used and where it gets used is very important to us.”Tim Friedlander, president of National Association of Voice Actors
</blockquote>



<hr class="wp-block-separator has-alpha-channel-opacity"/>



After ElevenLabs rolled out the beta version of its text-to-speech AI tool in January, the startup&nbsp;<a href="https://twitter.com/elevenlabsio/status/1620032627075063811" target="_blank" rel="noreferrer noopener">announced</a>&nbsp;that it was struggling with people misusing its technology. A day later, Vice’s Motherboard&nbsp;<a href="https://www.vice.com/en/article/dy7mww/ai-voice-firm-4chan-celebrity-voices-emma-watson-joe-rogan-elevenlabs" target="_blank" rel="noreferrer noopener">found</a>&nbsp;that anonymous 4Chan posters used ElevenLabs’ then free cloning tool to generate racist, transphobic and violent remarks with the voices of celebrities like Joe Rogan and Emma Watson.



AI’s ability to closely mimic people’s voices has also created opportunities for scammers. The FTC has issued&nbsp;<a href="https://consumer.ftc.gov/consumer-alerts/2023/03/scammers-use-ai-enhance-their-family-emergency-schemes" target="_blank" rel="noreferrer noopener">warnings</a>&nbsp;this year that criminals are using AI voice clones to impersonate loved ones as a way to convince their targets to send them money. One journalist was able to use ElevenLabs’ tool to create an AI-generated version of his voice that&nbsp;<a href="https://www.vice.com/en/article/dy7axa/how-i-broke-into-a-bank-account-with-an-ai-generated-voice" target="_blank" rel="noreferrer noopener">successfully</a>&nbsp;logged into his own bank account.



ElevenLabs did not comment on any of these specific instances, but CEO Staniszewski said in an email, “If someone is using our tool to clone voices for which they don’t have permission and which contravene fair use cases, we will ban the account and prevent new accounts from being set up with the same details.” Along with a “voice captcha” tool to ensure people have that permission, the company says it has also developed an AI speech classifier that can detect with more than 90% accuracy whether an audio clip that contains AI was made using its tools.



<hr class="wp-block-separator has-alpha-channel-opacity"/>



<h2 class="wp-block-heading" id="h-consent-and-control">Consent And Control</h2>



In response to misuse, voice generation sites are adding restrictive measures to police their technologies. Speechify, which licenses the voices of celebrity narrators like Snoop Dog and Gwyneth Paltrow (with full permission), doesn’t allow people to upload content to create customized voices without the active participation of the person whose voice they want to use. Similar to ElevenLabs, it presents a unique text that the user, or someone who is physically present with them, has to read aloud in their own voice. “I think it is short sighted to take shortcuts and my goal is to put content owners in the driver&#8217;s seat,” said founder Cliff Weitzman, who first started Speechify to convert his textbooks into audiobooks using machine learning in 2012.



And at Resemble AI, which touts enterprise customers like Netflix and World Bank Group, people can only create a customized AI-generated voice after recording a consent statement in the voice they want to generate. Resemble AI founder and CEO Zohaib Ahmed said that implementing safe ways to deploy the technology has been integral to his startup because he believes the onus of preventing misuse should fall on the vendors making the tools rather than on the end user.



<hr class="wp-block-separator has-alpha-channel-opacity"/>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
“It sucks that we have no personal ownership of our voices.”Allegra Clark, voice actor
</blockquote>



These kinds of verification checks, however, don’t address higher level ethical questions around consent. Actors, for instance, don’t really have control over how their voices will be used posthumously. Voice actors were enraged when&nbsp;<a href="https://www.gamesradar.com/after-backlash-over-using-ai-to-clone-dead-voice-actors-smite-and-paladins-studio-says-it-will-change-its-contract/" target="_blank" rel="noreferrer noopener">gaming studio</a>&nbsp;Hi-Rez Studios added a clause that would allow it to clone a voice using AI after the owner of the voice died (the clause was removed after the uproar). “If an actor passes away, it’s better to replace them with another human than create some artificial performance because it&#8217;s not them and it doesn&#8217;t bring them back,” said voice actor Clark.



The big concern hovering over all of this is whether there’s a future for voice actors. With employers and fans turning to synthesized voices, many are concerned about finding their next gig or keeping the ones they have. “Controlling how our voice gets used and where it gets used, and how much we&#8217;re paid for that usage is very important to us,” said NAVA’s Friedlander.

Voiceover artist voice actor in vocal recording studio with larg diaphragm microphone and antipop shield.

‘Keep Your Paws Off My Voice’: Voice Actors Worry Generative AI Will Steal Their Livelihoods

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



Spotify will start using artificial intelligence to translate podcasts into other languages, the company announced Monday as part of a partnership with OpenAI, as Spotify becomes the latest to use generative AI for its products.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



Spotify&nbsp;<a href="https://newsroom.spotify.com/2023-09-25/ai-voice-translation-pilot-lex-fridman-dax-shepard-steven-bartlett/" target="_blank" rel="noreferrer noopener">announced</a>&nbsp;Monday that it is releasing a pilot for its “Voice Translation” feature, which will translate podcasts into other languages that will match the original speaker’s voice and style.



The feature was created in partnership with OpenAI, which&nbsp;<a href="https://openai.com/blog/chatgpt-can-now-see-hear-and-speak" target="_blank" rel="noreferrer noopener">announced</a>&nbsp;Monday that it was releasing new “voice and image capabilities” for ChatGPT, allowing users to speak with the AI chatbot with generated “human-like audio from just text and a few seconds of sample speech.”



Spotify’s new feature is based on OpenAI’s voice transcription tool Whisper, which transcribes English speech and translates other languages into English.



The pilot includes three podcast episodes—including the&nbsp;Lex Fridman Podcast,&nbsp;Armchair Expert&nbsp;and&nbsp;The Diary of a CEO with Steven Bartlett—available in Spanish to both subscribed and unsubscribed users, with episodes available in French and German “in the coming days and weeks.”



All translated podcasts will be available in Spotify’s “<a href="https://spoti.fi/VoiceTranslation" target="_blank" rel="noreferrer noopener">Voice Translations Hub</a>,” which will be updated with additional episodes and podcasts “over the coming weeks and months.”



<h2 class="wp-block-heading" id="h-big-number">BIG NUMBER</h2>



100 million. That’s how many users “regularly” listen to podcasts on Spotify, according to the company.



<h2 class="wp-block-heading" id="h-key-background">KEY BACKGROUND</h2>



Other companies have started to use generative AI for its products in recent months. Meta&nbsp;<a href="https://www.forbes.com/sites/irenebenedicto/2023/08/02/meta-launches-tool-to-create-music-using-ai-heres-what-to-know/?sh=4eddc404444d">announced</a>&nbsp;earlier this year that it would release AudioCraft, a tool that allows users to create AI-generated music and sounds. The&nbsp;<a href="https://www.ft.com/content/6f022306-2f83-4da7-8066-51386e8fe63b?list=intlhomepage" target="_blank" rel="noreferrer noopener">Financial Times</a>&nbsp;reported in August that Google and Universal Music Group were in discussions over whether to license artists’ melodies and vocals for AI-generated music. Google also&nbsp;<a href="https://www.forbes.com/sites/tylerroush/2023/09/19/google-expands-ai-chatbot-bard-to-apps-like-gmail-drive-and-youtube/?sh=3282847f4905">announced</a>&nbsp;earlier this month that it had integrated its AI chatbot Bard into its other applications, including YouTube, Gmail and Drive. Amid concerns over privacy and safety, OpenAI said it was gradually releasing its image and voice capabilities for ChatGPT, after the company warned the new features could present new risks, including “the potential for malicious actors to impersonate public figures or commit fraud.”



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<h2 class="wp-block-heading" id="h-further-reading">FURTHER READING</h2>



<a href="https://www.forbes.com/sites/tylerroush/2023/08/08/google-and-universal-music-group-negotiating-ai-generated-music-tool-report-says/?sh=3d4d29cf22e7">Google And Universal Music Group Negotiating AI-Generated Music Tool, Report Says</a>&nbsp;(Forbes)



<a href="https://www.forbes.com/sites/irenebenedicto/2023/08/02/meta-launches-tool-to-create-music-using-ai-heres-what-to-know/?sh=4eddc404444d">Meta Launches Tool To Create Music Using AI—Here’s What To Know</a> (Forbes)<a href="https://www.forbes.com/sites/tylerroush/"></a>

Tag: artificial intelligence

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