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The term ‘ethical AI’ is finally starting to mean something

Since OpenAI first described its new AI language-generating system called GPT-3 in May, hundreds of media outlets (including MIT Technology Review) have written about the system and its capabilities. Twitter has been abuzz about its power and potential. The New York Times published an op-ed about it. Later this year, OpenAI will begin charging companies for access to GPT-3, hoping that its system can soon power a wide variety of AI products and services.


Earlier this year, the independent research organisation of which I am the Director, London-based Ada Lovelace Institute, hosted a panel at the world’s largest AI conference, CogX, called The Ethics Panel to End All Ethics Panels. The title referenced both a tongue-in-cheek effort at self-promotion, and a very real need to put to bed the seemingly endless offering of panels, think-pieces, and government reports preoccupied with ruminating on the abstract ethical questions posed by AI and new data-driven technologies. We had grown impatient with conceptual debates and high-level principles.

And we were not alone. 2020 has seen the emergence of a new wave of ethical AI – one focused on the tough questions of power, equity, and justice that underpin emerging technologies, and directed at bringing about actionable change. It supersedes the two waves that came before it: the first wave, defined by principles and dominated by philosophers, and the second wave, led by computer scientists and geared towards technical fixes. Third-wave ethical AI has seen a Dutch Court shut down an algorithmic fraud detection system, students in the UK take to the streets to protest against algorithmically-decided exam results, and US companies voluntarily restrict their sales of facial recognition technology. It is taking us beyond the principled and the technical, to practical mechanisms for rectifying power imbalances and achieving individual and societal justice.

Between 2016 and 2019, 74 sets of ethical principles or guidelines for AI were published. This was the first wave of ethical AI, in which we had just begun to understand the potential risks and threats of rapidly advancing machine learning and AI capabilities and were casting around for ways to contain them. In 2016, AlphaGo had just beaten Lee Sedol, promoting serious consideration of the likelihood that general AI was within reach. And algorithmically-curated chaos on the world’s duopolistic platforms, Google and Facebook, had surrounded the two major political earthquakes of the year – Brexit, and Trump’s election.

GPT-3, Bloviator: OpenAI’s language generator has no idea what it’s talking about

Since OpenAI first described its new AI language-generating system called GPT-3 in May, hundreds of media outlets (including MIT Technology Review) have written about the system and its capabilities. Twitter has been abuzz about its power and potential. The New York Times published an op-ed about it. Later this year, OpenAI will begin charging companies for access to GPT-3, hoping that its system can soon power a wide variety of AI products and services.

Is GPT-3 an important step toward artificial general intelligence—the kind that would allow a machine to reason broadly in a manner similar to humans without having to train for every specific task it encounters? OpenAI’s technical paper is fairly reserved on this larger question, but to many, the sheer fluency of the system feels as though it might be a significant advance.

We doubt it. At first glance, GPT-3 seems to have an impressive ability to produce human-like text. And we don’t doubt that it can used to produce entertaining surrealist fiction; other commercial applications may emerge as well. But accuracy is not its strong point. If you dig deeper, you discover that something’s amiss: although its output is grammatical, and even impressively idiomatic, its comprehension of the world is often seriously off, which means you can never really trust what it says.

Pentagon approves five US drone makers ahead of likely ban on China’s DJI

Ahead of a likely ban on the US federal government’s use of Chinese-made quadcopters, including popular DJI drones, the Department of Defense has approved the products of five US-based unmanned air vehicle (UAV) makers for government use.

Those companies are Altavian, Parrot, Skydio, Teal and Vantage Robotics.

Small UAVs from these manufacturers have been deemed cyber-secure by the Pentagon – not vulnerable to backdoor spying that some suspect might be possible from the video cameras and other sensors attached to Chinese-made DJI drones. The US Congress is considering banning the US federal government from using foreign-made drones as part of its 2021 National Defense Authorization Act.

Facebook is training robot assistants to hear as well as see

In June 2019, Facebook’s AI lab, FAIR, released AI Habitat, a new simulation platform for training AI agents. It allowed agents to explore various realistic virtual environments, like a furnished apartment or cubicle-filled office. The AI could then be ported into a robot, which would gain the smarts to navigate through the real world without crashing.

In the year since, FAIR has rapidly pushed the boundaries of its work on “embodied AI.” In a blog post today, the lab has announced three additional milestones reached: two new algorithms that allow an agent to quickly create and remember a map of the spaces it navigates, and the addition of sound on the platform to train the agents to hear.

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