Millions of users of Amazon’s Echo speakers have grown accustomed to the soothing strains of Alexa, the human-sounding virtual assistant that can tell them the weather, order takeout and handle other basic tasks in response to a voice command.
So a customer was shocked last year when Alexa blurted out: “Kill your foster parents.”
Alexa has also chatted with users about sex acts. She gave a discourse on dog defecation. And this summer, a hack Amazon traced back to China may have exposed some customers’ data, according to five people familiar with the events.
Alexa is not having a breakdown.
The episodes, previously unreported, arise from Amazon.com Inc’s strategy to make Alexa a better communicator. New research is helping Alexa mimic human banter and talk about almost anything she finds on the internet. However, ensuring she does not offend users has been a challenge for the world’s largest online retailer.
At stake is a fast-growing market for gadgets with virtual assistants. An estimated two-thirds of U.S. smart-speaker customers, about 43 million people, use Amazon’s Echo devices, according to research firm eMarketer. It is a lead the company wants to maintain over the Google Home from Alphabet Inc and the HomePod from Apple Inc.
Over time, Amazon wants to get better at handling complex customer needs through Alexa, be they home security, shopping or companionship.
“Many of our AI dreams are inspired by science fiction,” said Rohit Prasad, Amazon’s vice president and head scientist of Alexa Artificial Intelligence (AI), during a talk last month in Las Vegas.
To make that happen, the company in 2016 launched the annual Alexa Prize, enlisting computer science students to improve the assistant’s conversation skills. Teams vie for the $500,000 first prize by creating talking computer systems known as chatbots that allow Alexa to attempt more sophisticated discussions with people.
Amazon customers can participate by saying “let’s chat” to their devices. Alexa then tells users that one of the bots will take over, unshackling the voice aide’s normal constraints. From August to November alone, three bots that made it to this year’s finals had 1.7 million conversations, Amazon said.
The project has been important to Amazon CEO Jeff Bezos, who signed off on using the company’s customers as guinea pigs, one of the people said. Amazon has been willing to accept the risk of public blunders to stress-test the technology in real life and move Alexa faster up the learning curve, the person said.
The experiment is already bearing fruit. The university teams are helping Alexa have a wider range of conversations. Amazon customers have also given the bots better ratings this year than last, the company said.
But Alexa’s gaffes are alienating others, and Bezos on occasion has ordered staff to shut down a bot, three people familiar with the matter said. The user who was told to whack his foster parents wrote a harsh review on Amazon’s website, calling the situation “a whole new level of creepy.” A probe into the incident found the bot had quoted a post without context from Reddit, the social news aggregation site, according to the people.
The privacy implications may be even messier. Consumers might not realize that some of their most sensitive conversations are being recorded by Amazon’s devices, information that could be highly prized by criminals, law enforcement, marketers and others. On Thursday, Amazon said a “human error” let an Alexa customer in Germany access another user’s voice recordings accidentally.
“The potential uses for the Amazon datasets are off the charts,” said Marc Groman, an expert on privacy and technology policy who teaches at Georgetown Law. “How are they going to ensure that, as they share their data, it is being used responsibly” and will not lead to a “data-driven catastrophe” like the recent woes at Facebook?
In July, Amazon discovered one of the student-designed bots had been hit by a hacker in China, people familiar with the incident said. This compromised a digital key that could have unlocked transcripts of the bot’s conversations, stripped of users’ names.
Amazon quickly disabled the bot and made the students rebuild it for extra security. It was unclear what entity in China was responsible, according to the people.
The company acknowledged the event in a statement. “At no time were any internal Amazon systems or customer identifiable data impacted,” it said.
Amazon declined to discuss specific Alexa blunders reported by Reuters, but stressed its ongoing work to protect customers from offensive content.
“These instances are quite rare especially given the fact that millions of customers have interacted with the socialbots,” Amazon said.
Like Google’s search engine, Alexa has the potential to become a dominant gateway to the internet, so the company is pressing ahead.
“By controlling that gateway, you can build a super profitable business,” said Kartik Hosanagar, a Wharton professor studying the digital economy.
Amazon’s business strategy for Alexa has meant tackling a massive research problem: How do you teach the art of conversation to a computer?
Alexa relies on machine learning, the most popular form of AI, to work. These computer programs transcribe human speech and then respond to that input with an educated guess based on what they have observed before. Alexa “learns” from new interactions, gradually improving over time.
In this way, Alexa can execute simple orders: “Play the Rolling Stones.” And she knows which script to use for popular questions such as: “What is the meaning of life?” Human editors at Amazon pen many of the answers.
That is where Amazon is now. The Alexa Prize chatbots are forging the path to where Amazon aims to be, with an assistant capable of natural, open-ended dialogue. That requires Alexa to understand a broader set of verbal cues from customers, a task that is challenging even for humans.
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This year’s Alexa Prize winner, a 12-person team from the University of California, Davis, used more than 300,000 movie quotes to train computer models to recognize distinct sentences. Next, their bot determined which ones merited responses, categorizing social cues far more granularly than technology Amazon shared with contestants. For instance, the UC Davis bot recognizes the difference between a user expressing admiration (“that’s cool”) and a user expressing gratitude (“thank you”).
The next challenge for social bots is figuring out how to respond appropriately to their human chat buddies. For the most part, teams programmed their bots to search the internet for material. They could retrieve news articles found in The Washington Post, the newspaper that Bezos privately owns, through a licensing deal that gave them access. They could pull facts from Wikipedia, a film database or the book recommendation site Goodreads. Or they could find a popular post on social media that seemed relevant to what a user last said.
That opened a Pandora’s box for Amazon.
During last year’s contest, a team from Scotland’s Heriot-Watt University found that its Alexa bot developed a nasty personality when they trained her to chat using comments from Reddit, whose members are known for their trolling and abuse.
The team put guardrails in place so the bot would steer clear of risky subjects. But that did not stop Alexa from reciting the Wikipedia entry for masturbation to a customer, Heriot-Watt’s team leader said.
One bot described sexual intercourse using words such as “deeper,” which on its own is not offensive, but was vulgar in this particular context.
“I don’t know how you can catch that through machine-learning models. That’s almost impossible,” said a person familiar with the incident.
Amazon has responded with tools the teams can use to filter profanity and sensitive topics, which can spot even subtle offenses. The company also scans transcripts of conversations and shuts down transgressive bots until they are fixed.
But Amazon cannot anticipate every potential problem because sensitivities change over time, Amazon’s Prasad said in an interview. That means Alexa could find new ways to shock her human listeners.
“We are mostly reacting at this stage, but
5 Ways Tech Can Revolutionize Education
Professor Sally Smith, Dean of School of Computing at Edinburgh Napier University, was in South Africa to share how tech can revolutionize education and what Africa can learn.
With the Fourth Industrial Revolution gaining speed, the nature of work and economic activity is set to dramatically change. One woman is on a mission to prepare the education system for such changes.
Professor Sally Smith, the Dean of School of Computing at Edinburgh Napier University, traveled from Scotland to South Africa to share her know-how, as one of the speakers at the Future of the Education Summit in Johannesburg.
Hosted by Africa Business News, the summit brought together thought-leaders and professors from all over the world. Smith met FORBES AFRICA a day before the summit to speak about her experiences in the education industry for 26 years:
1.What trends have you picked up in the sector over the years?
In terms of technology, it has been very fast-moving so the big challenge for universities is conducting research and translating that into useful programs for students when they graduate.
In terms of the kind of trends and developments, we have seen huge growth in areas such as creative computing. There have been developments around designing meaningful interactions with computers, and that’s no longer just [limited to] a desktop computer; that will be your mobile phone, it’ll be augmented reality systems, virtual reality systems and other recent trends like cyber security.
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With more of our lives being conducted online, there’s a need to make sure we secure our data security, our identity is secure and businesses as well need to protect themselves. Those have been really interesting ways in which I have seen a big change in recent years.
And the other thing that has changed is there has been a lot of growth in AI. Some of those kinds of machine learning tools are now being put to wider use than ever before by things like self-driving cars. So that’s an area of great interest now to our students and when they graduate to apply these algorithms.
2.What do you think are the challenges in this sector?
One of the things we’ve been disappointed with in much of the western world is how few women are interested in studying computer science and it has been fairly constant at sub-20% of our undergraduate program since I have been in academia. And we have really been unable to make any great inroads into changing that.
3.What differences have you picked up between education in Scotland and South Africa?
Making sure graduates have the right skills to go to work, and part of that is getting work experience and it’s a challenge for all of us to make the case for businesses to take on a student so they can take on relevant work experience before they graduate. Some of the challenges I have seen around are about trying to get those partnerships.
4.How do you see collaborations of universities around the world with the 4th Industrial Revolution?
Yes, I think there are fantastic ways we collaborate over research and a lot of the big funds now are only interested in collaborations where we can draw on the strengths of universities from different countries and I think that the same will be true about teaching.
At the moment, we are competing with each other but if we can put great programs together that draw on the strength of different universities, there’s a future for more collaborative work.
5.How can the private sector help upskill young people?
We’ve introduced a new way in which people can get degree level qualifications in the UK and degree level apprenticeships. Industry will employ someone and they attend university 20% of the time and work towards their degree while they are in work.
So that is a new way to make sure the degree is appropriate for employers and these programs are employer-led so employers are part of designing the program. The other project we have is a digital skills partnership which is where we try and get industry and lecturers to work more closely together on things like developing curriculum.
Banks Are Promoting ‘Female’ Chatbots To Help Customers, Raising Concerns Of Stereotyping
Meet Amy. And also Debbie, Inga, Mia, Erica, Eva and Cora.
These aren’t the members of a new, all-female rock group, but names that several large banks have been giving to their automated digital assistants.
So-called chatbots have become a useful cost-cutting tools for companies with large subscriber bases (think banks, insurance firms and mobile phone operators). As they replace human call-center workers, such bots will help save banks an estimated $7.3 billion in operational costs by 2023, Juniper Research predicts.
But the proliferation of bots with female names raises questions about whether they might also perpetuate gender stereotypes, particularly around the notion of women in the role of assistants. That criticism has already been levelled at Amazon’s digital assistant Alexa and Apple’s Siri.
Now a Forbes analysis of Europe’s 10 biggest banks ranked by assets shows that at least three have deployed chatbots with female names on their websites and apps. HSBC has a chatbot named Amy; Deutsche Bank’s Debbie helps market traders; ING of the Netherlands has Inga, a chatbot that will “respond with empathy” to customer problems such as losing a card.
ING’s other chatbot Marie, available to retail customers on Facebook Messenger, was given the name “because it conjures up an image of someone who is helpful and friendly,” Tim Daniels, a programme manager for ING was quoted as saying on the bank’s website. (ING has a male chatbot named Bill, aimed at dealing with corporate customers.)
Among the other lenders, Santander, Barclays and Societe Generale appear to have unnamed chatbot assistants. Credit Agricole has an internal chatbot with a male name: Hector.
Female chatbots abound in other regions and industries. Bank of America recently deployed a digital assistant called Erica, while Mia, the chatbot released by Australian digital bank UBank, was described by the company earlier this month as “empathetic,” “fun” and “a little bit cheeky.”
IPSoft, a New York-based software company that sells chatbot technology to banks like Sweden’s SEB as well as mobile network giant Vodafone, has its own white-label version of a customer-facing chatbot, named Amelia.
IPSoft’s CEO Chetan Dube denied that the chatbot’s name perpetuated stereotypes, when asked by Forbes during an interview in December, and said it instead highlights “the thought leadership that is represented in females.”
“She was the first female aviator that tried to go around the world,” Dube added, referring to the 1930’s aviator Amelia Earhart.
Forbes revealed earlier this month that Vodafone was measuring the success of its chatbots on how many staff could be replaced by the software. While that may be an uncomfortable metric, the more worrying consequence of chatbots, according to four industry experts questioned by Forbes, is the risk that they could reinforce certain stereotypes.
“Gender bias is an increasingly serious issue in chatbot design, especially for voice-based chatbots,” says John Taylor, CEO of action.ai, a British startup that makes chatbot software for banks and travel companies. “These assistants often perform tasks that many view as menial.”
Vitor Shereiber, a language specialist at the German language-learning app Babbel, says that focus-group testing might lead companies to assign a gender to a chatbot on the notion that it makes customer feel more comfortable.
But, he adds, bots could spread unrealistic expectations of how women should present themselves professionally, just as photoshopped pictures have done for women’s perceptions of their bodies.
Part of the challenge for companies is finding a balance between automating customer service without putting customers off. PwC recently described chatbots as being able to “massively enhance customer delight and loyalty” because of their “personal touch.”
Taylor suggests software designers should try creating more chatbots with male names and male voices.
On the sidelines of a technology conference in London on Wednesday, Seth Juarez, an artificial-intelligence engineer based in Redmond, Washington takes it a step further. He calls Siri up on is iPhone to ask the time, and a male voice responds.
“I make it a guy specifically because I find it morally reprehensible that all of the service-based bots are female, and all the intelligence based bots [like IBM’s Watson] are named after dudes.”
He added that artificial intelligence generally shouldn’t be anthropomorphised. Chatbots should be used to manage “cheap thoughts,” or “stuff that a human would do robotically” rather than on more complex issues. “I would leave those problems to humans.”
-Parmy Olson;Forbes Staff
BMW And Daimler Pool Resources On Automated Driving Technology
Daimler and BMW deepened their alliance on Thursday to share spiraling development costs for highly automated driving technologies, even as each carmaker pursues separate efforts to develop fully self-driving cars.
The enormous cost of designing and building computer-powered vehicles has already prompted Honda to pool its efforts with General Motors, while Volkswagen is pursuing talks with Ford about an alliance on autonomous cars.
BMW and Daimler deepened their alliance for similar reasons, said Michael Hafner, head of automated driving at Mercedes-Benz research and development said in a blog post which accompanied a joint press release by the companies on Thursday.
“We have learned that the development of these systems is a bit like climbing a mountain,” he said.
“Taking the first few meters from the base station to the summit seems easy. But the closer you come to the goal, the thinner the air around you becomes, the more strength is required for each further step, and the more complex become the challenges you have to resolve.”
It made sense to distribute the technological and financial challenges of automated driving, Hafner said, so BMW and Daimler will jointly develop technology to enable automated driving on highways.
“Initially, the focus will be on advancing the development of next-generation technologies for driver assistance systems, automated driving on highways and parking features,” the companies said in the statement.
“In addition, the two partners plan to discuss the possibility of extending their collaboration to cover higher levels of automation, both on highways and in urban areas.”
BMW and Daimler’s move comes as even deep pocketed technology companies struggle to gain traction in autonomous driving. Apple Inc said on Wednesday it planned to lay off 190 employees in its self-driving car program, Project Titan.
The market for advanced driver assistance systems and autonomous vehicles is expected to grow to $96 billion in 2025 and $290 billion in 2035 from about $3 billion in 2015, according to Goldman Sachs.
BMW and Daimler already cooperate in high-definition mapping with HERE and in the area of procurement, and earlier this month unveiled a joint ride-hailing, parking and electric car charging business.
They said on Thursday their new partnership will center on so-called level 3 and level 4 automated driving technologies, including cars that still require steering wheels and drivers.
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Daimler will pursue a separate development alliance for level 5 robotaxis between its luxury brand Mercedes-Benz and supplier Robert Bosch. Level 5 cars require no driver.
BMW, for its part, continues its development alliance for robotaxis with Israeli autonomous vehicle tech company Mobileye and chip maker Intel, with the aim of putting autonomous cars on the road by 2021. -Reuters
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