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Understanding the real innovation behind the iPhone

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When the iPhone emerged in 2007, it came with all the promise and pomp of a major Steve Jobs announcement, highlighting its user interface and slick design as key selling points. We know now that the iPhone transformed the mobile phone business, the internet economy and, in many ways, society as a whole. But technically speaking, the iPhone was not very innovative.

Its software and the interface idea were based on the iPod, which was already reinventing the digital music industry. Touchscreens had appeared on earlier phone and tablet models, including Apple’s own Newton. And top-line Nokia phones had more memory, better cameras and faster mobile connectivity. What made the iPhone transformative was the shift in concept underpinning the entire iPhone project: Its designers did not create a telephone with some extra features, but rather a full-fledged hand-held computer that could also make calls and browse the internet.

As a scholar of management, design and innovation, I find it hard to predict what the next truly revolutionary technological development will be. In the 10 years since the launch of the iPhone, so much about modern life, commerce and culture has changed. In part that’s because the iPhone, and the smartphone boom it spurred, created a portable personal technology infrastructure that’s almost infinitely expandable. The iPhone changed the game not because of its initial technology and cool user interface but rather as a result of its creators’ imagination and courage.

Inventing mobile apps

As the iPhone took shape, its designers found themselves torn between making a phone or a computer. Engineers and marketing executives alike worried the new device would kill the iPod market that had driven Apple’s corporate resurgence for five years. Nokia, the biggest player in the cellphone market at the time, had similar technologies and prototypes, and also feared outcompeting its own successful mobile phone product lines that used a simpler and more old-fashioned software platform than that on which iPhone was built.

Apple took the leap, however, by installing a fully capable computer operating system on the iPhone, along with a few small application programs. Some were phone-related, including a program that handled making and receiving calls, as well as a new way to display voicemail messages, and a system that kept different contacts’ text messages separate. Others were more computer-like, including an email app and a web browser. Of course, the music-playing features from the iPod were included too, linking the phone with the emerging Apple music ecosystem.

Initially, that was about it for apps. But skilled computer engineers and hackers knew they were holding a palm-sized computer, and set to work writing their own software and getting it running on their iPhones. That was the dawn of the now-ubiquitous app. Within a year, these apps were so popular, and their potential so significant, that Apple’s second version of the iPhone operating system made it easy (and legal) for users to install apps on their phones.

Shifting priorities

The prospect of making a fully functional hand-held computer changed how users and manufacturers alike thought about mobile phones. For Apple and every other phone company, software became much more important than hardware. What apps a phone could run, and how quickly, mattered much more than whether it had a slightly better camera or could hold a few more photos; whether it flipped open, slid open or was a bar-style; or whether it had a large keyboard or a small one. The iPhone’s keyboard was on-screen and software-generated, making a function that had required dedicated hardware into one running on generic hardware and dedicated software.

At the time of the iPhone launch, Nokia offered about 200 different phone styles to meet all the different needs of its hundreds of millions of customers. There was just one iPhone model at the start, and in the ensuing decade there have been only 14 major styles – though today they come in different colors, not just white and black as the original did. This is the power of software functionality and related simplicity.

The heightened importance of software on a mobile phone shifted the industry’s economy as well. The money came now not just from selling devices and phone services, but also from marketing and selling apps and in-app advertisements. App developers must share revenue with the companies that control smartphones’ operating systems, providing serious earning power: Apple holds about 15% of the mobile phone market, but reaps 80% of global smartphone profits.

Whatever the next tech industry game-changer is, and whenever it arrives, it will likely have some connection to the smartphone and related infrastructure. Even today, exploring virtual reality requires only installing an app and connecting just a bit of additional hardware to an existing phone. Similarly, smartphone interfaces and cameras already monitor and control intelligent and automated homes. Even as devices are developed to operate all around us, and even in our clothes, many of them will be able to point to the iPhone as a conceptual ancestor and inspiration.  – Written by Kalle LyytinenIris S. Wolstein Professor of Management Design, Case Western Reserve University

Originally published in The Conversation

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How Virtual Therapy Apps Are Trying To Disrupt The Mental Health Industry

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Millions of Americans deal with mental illness each year, and more than half of them go untreated. As the mental health industry has grown in recent years, so has the number of tech startups offering virtual therapy, which range from online and app-based chatbots to video therapy sessions and messaging. 

Still a nascent industry, with most startups in the early seed-stage funding round, these companies say they aim to increase access to qualified mental health care providers and reduce the social stigma that comes with seeking help. 

While the efficacy of virtual therapy, compared with traditional in-person therapy, is still being hotly debated, its popularity is undeniable. Its most recognizable pioneers, BetterHelp and TalkSpace, have enrolled nearly 700,000 and more than 1 million users respectively. And investors are taking notice.

Funding for mental health tech startups has boomed in the past few years, jumping from roughly $100 million in 2014 to more than $500 million in 2018, according to Pitchbook. In May of this year, the subscription-based online therapy platform Talkspace raised an additional $50 million, bringing its total funding to just under $110 million since its 2012 inception.

The ubiquity of smartphones, coupled with the lessening of the stigma associated with mental health treatment have played a large role in the growing demand for virtual therapy. Of the various services offered on the Talkspace platform, “clients by far want asynchronous text messaging,” says Neil Leibowitz, the company’s chief medical officer.

Users seem to prefer back-and-forth messaging that isn’t restricted to a narrow window of time over face-to-face interactions. At BetterHelp, founder Alon Matas notes that older users are more likely to go for phone and video therapy sessions, whereas younger users favor text messaging.

“Each generation is getting progressively more mobile-native,” says John Prendergass, an associate director at Ben Franklin Technology Partners’ healthcare investment group, “so I think we’re going to see people become increasingly more accustomed, or predisposed, to a higher level of comfort in seeking care online.”

The ease and convenience of virtual therapy is another draw, particularly for busy people or those who live in rural areas with limited access to therapy and a range of care options.

Alison Darcy, founder and CEO of Woebot, a free automated chatbot that uses artificial intelligence to provide therapeutic services without the direct involvement of humans, says that with Woebot and other similar services, there is no need to schedule appointments weeks in advance and users can receive real-time coaching at the moment they need it, unlike traditional therapy. The sense of anonymity online can also lead to more openness and transparency and attracts people who normally wouldn’t seek therapy.

Along with stigma, the cost of therapy has historically acted as a barrier to accessing quality mental-health care. Health insurance is often unlikely to cover therapy sessions. In most cities, sessions run about $75 to $150 each, and can go as high as $200 or more in places like New York City. Web therapists don’t have to bear the expense of brick-and-mortar offices, filing paperwork or marketing their services, and these savings can be passed on to clients. 

BetterHelp offers a $200-a-month membership that includes weekly live sessions with a therapist and unlimited messaging in between, while Talkspace’s cheapest monthly subscription at $260-a-month, offers unlimited text, video and audio messaging.

But virtual therapy, particularly text-based therapy, is not suitable for everyone. Nor is it likely to make traditional therapy obsolete. “Online therapy isn’t good for people who have severe mental and relational health issues, or any kind of psychosis, deep depression or violence,” says Christiana Awosan, a licensed marriage and family therapist. 

At her New York and New Jersey offices, she works predominantly with black clients, a population that she says prefers face-to-face meetings. “This community is wary of mental health in general because of structural discrimination,” Awosan says. “They pay attention to nonverbal cues and so they need to first build trust in-person.”  

Virtual therapy apps can still be beneficial for people with low-level anxiety, stress or insomnia, and they can also help users become aware of harmful behaviors and obtain a higher sense of well-being. 

Sean Luo, a psychiatrist whose consultancy work focuses on machine learning techniques in mental health technology, says: “This why some of these companies are getting very high valuations. There are a lot of commercialization possibilities.” He adds that from a mental health treatment perspective, a virtual therapy app “isn’t going to solve your problems, because people who are truly ill will by definition require a lot more.”

Relying on digital therapy platforms might also provide a false sense of security for users who actually need more serious mental-health care, and many of these apps are ill-equipped to deal with emergencies like suicide, drug overdoses or the medical consequences of psychiatric illness. “The level of intervention simply isn’t strong enough,” says Luo, “and so these aspects still need to be evaluated by a trained professional.

Ruth Umoh, Diversity and Inclusion Writer, Forbes Staff.

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AI 50 Founders Say This Is What People Get Wrong About Artificial Intelligence

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Forbes’ new list of promising artificial intelligence companies highlights how the technology is creating real value across industries like transportation, healthcare, HR, insurance and finance.

Naturally, the founders of the honoree companies are excited about the technology’s benefits and, in their roles, spend a lot of time thinking and talking about its strengths and limitations. Here’s what they think people get wrong about artificial intelligence.

Affectiva CEO Rana el Kaliouby says she’s too often encountered the idea that AI is “evil.”

“AI—like any technology in history—is neutral,” she says. “It’s what we do with it that counts, so it’s our responsibility, as an AI ecosystem, to drive it in the right direction.” 

Companies need to be aware of how AI could widen bounds of inequality, she adds: “Any AI that is designed to interact with humans—Affectiva’s included—must be evaluated with regards to the ethical and privacy implications of these technologies.”

Sarjoun Skaff, CTO and cofounder of Bossa Nova Robotics, says that the biggest misconception he encounters is that artificial intelligence is actually, well, intelligent. 

“The truth is much more mundane,” he says. “AI is a very good pattern-matching tool. To make it work well, though, scientists need to understand the details of how it internally works and not treat it as an ‘intelligent’ black box. At the end of the day, making good use of great pattern matching still belongs to humans.”

Similarly, Aira cofounder Suman Kanuganti says that the public has “over-inflated expectations” for artificial intelligence.

“Garry Kasparov sums it up nicely: ‘We are in the beginning of MS-DOS and people think we are Windows 10,’” Kanuganti says. “AI realistically is still like a 3-year-old child at this stage. When it works, it feels magical. It does some things well, but there’s still a long way to go.”

So, no, we are nowhere close to “artificial general intelligence,” or AGI, where machines are actually as smart as humans.

“We’re still a long way from AI having the general intelligence of even a flea,” says David Gausebeck.

Despite the tendency to overestimate what artificial intelligence can do, the difficulty of building an effective system is often underestimated, some founders say.

“The systems you need to implement and manage machine learning in production are often much more complex than the algorithms themselves,” says Algorithmia CEO Diego Oppenheimer. “You can’t throw models at a complex business problem and expect returned value. You need to build an ecosystem to manage those models and connect their intelligence to your applications.” 

Put another way, you can’t just “sprinkle on some artificial intelligence like a magic sauce,” says Feedzai CEO Nuno Sebastiao.

One of the most common tropes that a handful of founders brought up was the idea that artificial intelligence is primarily a job killer.

People.ai founder Oleg Rogynskyy says that AI should be seen as a creator of new opportunities instead of a destroyer of jobs.

“In a nutshell, AI does two things: It automates repetitive low-value-add work for humans (which will indeed take low-complexity jobs away), which we think of as ‘Autopilot,’  and it guides people on how to do their work or other activities better (which makes humans more effective at what they do), which we call ‘Copilot,’” he says. “While Autopilot can take simple, repetitive and boring jobs away, Copilot is absolutely the best way to guide, train and educate humans on how to do new things.”

– By Jillian D’Onfro, Forbes

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‘AI Is A Powerful Tool’

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Research forecasts that by 2025, machines will perform more current work tasks than humans. Murat Sonmez, member of the managing board, and Head of the Centre for the WEF Fourth Industrial Revolution Network, expands on the role humans might play.


The Fourth Industrial Revolution (4IR) is at the center of the current economic frontier. In reality, is Africa prepared for such changes?

Moving quickly and being agile are key principles of success in the 4IR. Any country can succeed if they take on this mindset. A few years ago, Rwanda saw the opportunities drones, a 4IR technology, brought to their country.

They helped save over 800 lives by delivering blood to remote villages. To scale this, the government worked with the World Economic Forum’s (WEF) drones’ team to create the world’s first agile airspace regulation. Now, we see countries in Africa and around the world looking to the Rwandan model.

READ MORE | 5 Ways Tech Can Revolutionize Education

What feasible solutions can  artificial intelligence (AI) offer in terms of forecasting natural disasters, droughts food security on the African continent?

AI can help predict diseases, increase agriculture yields and help first responders. It is a powerful tool for governments and businesses, but it needs a lot of data to be effective.

For AI to be all that it can be, countries and companies need to work together to build frameworks for better management and protection of our data and ensure that it is shared and not stored in silos. Data is the oxygen of the (4IR). If countries do not leverage data and have their policies in place, they will be left behind.

There is a growing concern that the 4IR will strip people of jobs, of which there is already a shortage. How true is this?

The world is going through a workplace revolution that will bring a seismic shift in the way humans work alongside machines and algorithms.

Latest research from the WEF forecasts that by 2025, machines will perform more current work tasks than humans, compared to 71% being performed by humans today.

READ MORE | Roadmap For African Startups

The rapid evolution of machines and algorithms in the workplace could create 133 million new roles in place of 75 million that will be displaced between now and 2022.

Consumers have real concerns around the potential harm technology can cause in areas such as privacy, misinformation, surveillance, job loss, environmental damage and increased inequality. What ethical precautions are being considered in the robotics space?

Now more than ever, it is important to incorporate ethics into the design, deployment and use of emerging technology. Innovating in the 4IR requires addressing concerns around privacy and data ownership, while attracting the skills and forward-looking thinkers of the future.

There are big challenges and bigger opportunities ahead. We have seen many companies and countries create ethical and human rights-based frameworks. What’s important is they are co-designed with members of both communities along with academia, civil society and start-ups.

A multi-stakeholder approach will result in a more holistic set of guidelines and principles that can be adopted in many different industries and geographies.

READ MORE | It’s Time For Africa’s Gazelles To Shine

What changes need to take place for the African continent to be on par with global developments, and are there tangible goals set?

The 4IR provides governments the opportunity to be global leaders in shaping the next 20 to 30 years of science and technology. It is important they create an environment where companies can innovate.

The other tenet is to be open to working across borders and learning from each other. The global health industry has access to mountains of data on rare diseases, but it is trapped within countries and sometimes even within the hospital walls.

If we can build trust and find innovative ways to share the data while protecting privacy, we can employ tools like AI to help us cure disease faster. Countries and companies need to have the right governance frameworks and mechanisms in place for these breakthroughs to happen. It is possible to do these things now, but we need to work together to make it happen.

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