Skeptical insights about AI, including: AI is not neutral; AI usually relies on a lot of low-paid human labor; Don’t just talk about ethics, think about human rights; We need to hold government and corporations accountable; Questions designers using AI should ask.

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Lawyers, activists, and researchers emphasize the need for ethics and accountability in the design and implementation of AI systems. But this often ignores a couple of tricky questions: who gets to define those ethics, and who should enforce them? Technology often highlights peoples’ differing ethical standards. A crowd-sourced survey on moral decisions for self-driving cars showed huge variation across different cultures. Establishing ethical standards also doesn’t necessarily change behavior.

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To ensure that AI is developed, designed and adopted in ways that serve human wellbeing and the global social good. CATA is proposing 10 focus points for global consultation: Human Responsibility; Physical Integrity; Moral Integrity; Privacy; Neutrality; Mental Integrity; Wellbeing; Education; Ethical Behaviour; Skewing of Opinion.

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The 23 Principles developed in January 2017 at Asilomar, California, on beneficial AI to guide AI research. To date, the Principles have been signed by 1,273 AI/Robotics researchers and 2,541 others. 

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How should an autonomous artificial intelligence act when life is on the line? Philosopher James Moor categorizes machines into four ethical groups with different ethical abilities: Ethical impact agents, Implicit ethical agents, Explicit ethical agents, and Full ethical agents.

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AI has opened up a wealth of promising opportunities, but it has also led to the emergence of a mindset: ‘AI solutionism’, the philosophy that, given enough data, machine learning algorithms can solve all of humanity’s problems. This disregards important AI safety principles and sets unrealistic expectations about what AI can really do for humanity.

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A thoughtful review of Henry Kissinger’s article in The Atlantic, in which Kissinger questions whether we understand the consequences of such a sweeping technological revolution as AI represents. He fails to distinguish between the current narrow-AI and the future artificial general intelligence. But he has a valid concern that AI could end critical thought by humans (as computers have replaced arithmetic skills).

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Research shows women are better positioned than men to resist the automation of work and possibly even benefit from it. Women are overrepresented in industries that require high levels of social skills and empathy (such as nursing, teaching and care work). Women in advanced economies generally have higher levels of education and digital literacy, giving them a comparative advantage in a labour market that is continuously transformed by technological innovation.

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A Chinese professor argues that wealth disparity can be resolved by using AI to back central planning. An American economist argues that technology has destroyed capitalism and that technocrats need to lead a government, not be excluded from it.

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Learning to code won’t protect your job when computers become smart enough to build code for you—which is already starting to happen. Much code today is not that creative – it’s more like building LEGO bricks. There will still be a need for high-level coders, and for engineers solving difficult problems or performing important research.

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Google gave an amazingly lifelike demo of its Assistant making phonecall reservations for a haircut and for dinner at a restaurant. The British computer scientist, Alan Turing, devised the Turing test as a means of measuring whether a computer was capable of demonstrating intelligent behavior equivalent to or indistinguishable from that of a human. The second call could claim to have passed the test!

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Researchers from the University of Chicago have written a paper that shows how AI can be used to develop sophisticated reviews that are not only undetectable using contemporary methods but are also considered highly reliable by unwitting readers. They can be generated using a deep learning technique called recurrent neural networks, after being trained with thousands of real online reviews that are freely available online. A potential way to detect them would be to use character frequency analysis.

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MIT experts say we’ve entered “the second wave of the second machine age,” in which AI has exceeded expectations. The areas that AI will not easily handle include setting priorities and people management.

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More than 50% of US workers feel more stress than in 2016, with the fear of losing their job to AI the top stressor in the workplace. Outside of work, employees were most stressed by the current political climate, while inside the workplace they also felt unskilled for changing job demands. Training and development, meditation, and exercise were the top ways employees were combating stress.

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In September 2016, Facebook, Microsoft, IBM, Amazon, and Google announced the creation of a “Partnership on AI to Benefit People and Society” (Partnership on AI), a nonprofit formed to “study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.” Apple joined the partnership as a founding member in January 2017. 22 new organizations are joining including eBay, Intel, McKinsey, Salesforce, SAP, Sony, and 14 non-profits.

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The magnitude of the impact of AI in the next decade is way beyond anything we ever imagined. It is the real issue facing our government leaders today, as failure to transition to a sustainable AI society will lead to massive job loss and economic downturn. AI can recognize what is in an image; Beat the world champion at Go; Reproduce the style of any master artist; Understand natural language queries; Automate your house; Drive your car; Diagnose cancer better than a doctor; Recognize your kids in a picture better than you can yourself. Humans and Machines must be thought of as complementary. Many jobs will be transformed rather than disappear. Many high-paid jobs will also disappear. Solving the AI and Job crisis involves providing mass continuous education. We will change jobs as easily as we move houses.

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Some 80% of leading-edge consumers said they are excited about how technology developments such as AI, machine learning, and on-demand everything will impact their lives, according to a new report from Lippincott. These consumers embrace personalization over privacy and said they feel empowered by the constant support available from smart machines, AI, and robotics. Businesses can capitalize on this information about the customer of the future when making decisions about integrating AI and new technologies into products.

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“I believe there is no real difference between what can be achieved by a biological brain and what can be achieved by a computer,” said Hawking in a video appearance at the 2017 Global Mobile Internet Conference Beijing. “Humans, who are limited by slow biological evolution, couldn’t compete and could be superseded by AI,” he added. Leading Chinese companies in the ‘new’ economy are knee-deep in AI. Baidu (the Chinese equivalent of Google), Didi (China’s Uber rival), and Tencent (a maker of games and owner of messaging app giant WeChat) all have their own AI labs. Baidu apparently has as many as 1,300 staff in its AI division and is targeting a launch of its own self-driving cars in 2020.

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Fully autonomous driving has the potential to have as large an effect on our way of living as the car itself did. Ride-sharing allows purchasers to amortize the large capital cost over many drivers and high utilization, although safety drivers will be around for a long time. Adoption is going to be high as there becomes little incentive to own a car. Social impacts include Accident Avoidance (37,000 Americans die annualy in car accidents; 1.3m globally; 100x injured); Revamping of Insurance Industry; Commute times go down; Elimination of parking space frees land but reduces municipal revenue and policing time; c45% reduction in energy demand across all road transportation. Opportunities for new transportation technologies.

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Isaac Asimov’s 1942 “Three Laws of Robotics” formulated a set of logical parameters for rational ethical behavior that could be programmed into any artificial intelligence: 0) A robot may not harm humanity, or, by inaction, allow humanity to come to harm. 1) A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2) A robot must obey the orders given it by human beings except where such orders would conflict with the First Law. 3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

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