Delete All Your Apps

A good question to ask yourself when evaluating your apps is “why does this app exist?” If it exists because it costs money to buy, or because it’s the free app extension of a service that costs money, then it is more likely to be able to sustain itself without harvesting and selling your data. […]

Split learning for health: Distributed deep learning without sharing raw patient data

Can health entities collaboratively train deep learning models without sharing sensitive raw data? This paper proposes several configurations of a distributed deep learning method called SplitNN to facilitate such collaborations. SplitNN does not share raw data or model details with collaborating institutions. The proposed configurations of splitNN cater to practical settings of i) entities holding […]

First compute no harm

Is it acceptable for algorithms today, or an AGI in a decade’s time, to suggest withdrawal of aggressive care and so hasten death? Or alternatively, should it recommend persistence with futile care? The notion of “doing no harm” is stretched further when an AI must choose between patient and societal benefit. We thus need to […]

MIT researchers show how to detect and address AI bias without loss in accuracy

The key…is often to get more data from underrepresented groups. For example…an AI model was twice as likely to label women as low-income and men as high-income. By increasing the representation of women in the dataset by a factor of 10, the number of inaccurate results was reduced by 40 percent. Source: MIT researchers show […]

E.J. Chichilnisky | Restoring Sight to the Blind

Source: After on podcast with Rob Reid: Episode 39: E.J. Chichilnisky | Restoring Sight to the Blind. This was mind-blowing. The conversation starts with a basic overview of how the eye works, which is fascinating in itself, but then they start talking about how they’ve figured out how to insert an external (digital) process into […]

a16z Podcast: Network Effects, Origin Stories, and the Evolution of Tech

If an inferior product/technology/way of doing things can sometimes “lock in” the market, does that make network effects more about luck, or strategy? It’s not really locked in though, since over and over again the next big thing comes along. So what does that mean for companies and industries that want to make the new […]

The AI Threat to Democracy

With the advent of strong reinforcement learning…, goal-oriented strategic AI is now very much a reality. The difference is one of categories, not increments. While a supervised learning system relies upon the metrics fed to it by humans to come up with meaningful predictions and lacks all capacity for goal-oriented strategic thinking, reinforcement learning systems […]

PSA: Writing is hard

A few days ago I submitted a chapter for an edited collection on Speculative Futures for Artificial Intelligence and Educational Inclusion and I thought I’d take a moment to share some of my experience in writing it. When I talk about writing with colleagues I get the impression that they’re waiting for the moment when […]

When AI Misjudgment Is Not an Accident

The conversation about unconscious bias in artificial intelligence often focuses on algorithms that unintentionally cause disproportionate harm to entire swaths of society…But the problem could run much deeper than that. Society should be on guard for another twist: the possibility that nefarious actors could seek to attack artificial intelligence systems by deliberately introducing bias into […]

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