Pre-crime? Is refusing the ‘screening’ proof of mental illness?

Law Enforcement’s National Threat Assessment Program Predicts If You Pose A Future Threat

Joe Cadillic writes:

It has been nearly two years, since I reported on the dangers of creating a law enforcement run Mental Health Assessment (MHA) program. In Texas, police use MHA’s to “screen” every person they have arrested for mental illness.

But the TAPS Act, first introduced in January, would take law enforcement screenings to a whole new level. It would create a national threat assessment of children and adults.

In the course of six months the Threat Assessment, Prevention and Safety (TAPS) Act (H.R. 838) has seen support of the bill grow to nearly 80 Congress members.

Read more on MassPrivateI

Is this a massive privacy breach? I’m not sure.

CU Colorado Springs students secretly photographed for government-backed facial-recognition research

Elizabeth Hernandez follows up on a story that the Colorado Springs Independent broke last week:

A professor at the University of Colorado’s Colorado Springs campus led a project that secretly snapped photos of more than 1,700 students, faculty members and others walking in public more than six years ago in an effort to enhance facial-recognition technology.

The photographs were posted online as a dataset that could be publicly downloaded from 2016 until this past April.

Read more on the Denver Post.

Until AIs achieve peoplehood.

https://www.technologyreview.com/s/613578/ai-algorithms-liability-human-blame/

When algorithms mess up, the nearest human gets the blame

Earlier this month, Bloomberg published an article about an unfolding lawsuit over investments lost by an algorithm. A Hong Kong tycoon lost more than $20 million after entrusting part of his fortune to an automated platform. Without a legal framework to sue the technology, he placed the blame on the nearest human: the man who sold it to him.

It’s the first known case over automated investment losses, but not the first involving the liability of algorithms. In March of 2018, a self-driving Uber struck and killed a pedestrian in Tempe, Arizona, sending another case to court. A year later, Uber was exonerated of all criminal liability, but the safety driver could face charges of vehicular manslaughter instead.

Both cases tackle one of the central questions we face as automated systems trickle into every aspect of society: Who or what deserves the blame when an algorithm causes harm? Who or what actually gets the blame is a different yet equally important question.

Do you think Forbes knows something we don’t?

https://www.forbes.com/sites/steveandriole/2019/05/28/what-if-expert-systems-ruled-the-world-understanding-aiml-first-principles/#67d254a4688a

What If Artificial Intelligence (AI) & Machine Learning (ML) Ruled the World?

What if instead of political parties, presidents, prime ministers, kings, queens, armies, autocrats, and who knows what else, we turned everything over to expert systems? What if we engineered them to be faithful, for example, to one simple principle: "human beings regardless of age, gender, race, origin, religion, location, intelligence, income or wealth, should be treated equally, fairly and consistently"?

Here’s some dialogue – enabled by natural language processing (NLP) – with an expert system named “Decider” that operates from that single principle (you can imagine how it might behave if the principle was completely different – the opposite of equal and fair). The principle is supported by the data and probabilities the system collects and interprets. The “inferences” made by Decider are pre-programmed. In today’s political parlance, Decider is “liberal.” Imagine the one the American TEA Party or Freedom Caucus might engineer – which is the essence of this post: first principles rule.

Keep trying until we get it right (or until AI writes its own?)

https://theconversation.com/will-we-ever-agree-to-just-one-set-of-rules-on-the-ethical-development-of-artificial-intelligence-117744

Will we ever agree to just one set of rules on the ethical development of artificial intelligence?

Australia is among 42 countries that last week signed up to a new set of policy guidelines for the development of artificial intelligence (AI) systems.

Yet Australia has its own draft guidelines for ethics in AI out for public consultation, and a number of other countries and industry bodies have developed their own AI guidelines.

… Responding to these fears and a number of very real problems with narrow AI, the OECD recommendations are the latest of a number of projects and guidelines from governments and other bodies around the world that seek to instil an ethical approach to developing AI.

These include initiatives by the Institute of Electrical and Electronics Engineers, the French data protection authority, the Hong Kong Office of the Privacy Commissioner and the European Commission.