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So we can say that passing a well-crafted AI Citizenship Test would bea sufficient condition for possessing a high level of human-like general intelligenceNOT a necessary condition for possessing a high level of general intelligence; nor even a necessary condition for possessing a high level of human-like general intelligenceNOT a sufficient condition for possessing precisely human-like intelligence (as required by the Turing Test or other similar tests)These limitations, however, do not make the notion of an AI Citizenship less interesting; in a way, they make it more interesting. What they tell us is: An AI Citizenship Test will be a specific type of general intelligence test that is specifically relevant to key aspects of modern society.

If you would like to voice your perspectives on the AI Citizenship Test, please feel free to participate here.

If China, Russia and the U.S. are in a race for AI supremacy, the kind of manifestations of AI will be so significant, they could alter the entire future of human civilization.

THE EXPONENTIAL THREATFrom drones, to nanobots to 3D-printing, automation could lead to unparalleled changes to how we live and work. In spite of the increase in global GDP, most people’s quality of living is not likely to see the benefit as it will increasingly be funneled into the pockets of the 1%. Capitalism then, favors the development of an AI that’s fundamentally exploitative to the common global citizen.Just as we exchanged our personal data for convenience and the illusion of social connection online, we will barter convenience for a world a global police state where social credit systems and AI decide how much of a “human stipend” (basic income) we receive. Our poverty or the social privilege we are born into, may have a more obscure relationship to a global system where AI monitors every aspect of our lives.Eventually AI will itself be the CEOs, inventors, master engineers and creator of more efficient robots. That’s when we will know that AI has indeed replaced human beings. What will Google’s DeepMind be able to do with the full use of next-gen quantum computing and supercomputers?

Artificial Intelligence Will Replace HumansTo argue that AI and robots and 3D-printing and any other significant technology won’t impact and replace many human jobs, is incredibly irresponsible.That’s not to say humans won’t adapt, and even thrive in more creative, social and meaningful work!That AI replacing repetitive tasks is a good thing, can hardly be denied. But will it benefit all globally citizens equally? Will ethics, common sense and collective pragmatism and social inclusion prevail over profiteers?Will younger value systems such as decentralization and sustainable living thrive with the advances of artificial intelligence?Will human beings be able to find sufficient meaning in a life where many of them won’t have a designated occupation to fill their time?These are the question that futurists like me ponder, and you should too.

his company’s first move was to release a different gene-editing enzyme called MAD7—you can think of it like a Crispr/Cas9 knockoff, but legal—free for R&D uses. Inscripta will charge a single-digit royalty, far below market standards, to use MAD7 in manufacturing products or therapeutics.

We’re trying to get more people into the game now, by democratizing access to this family of enzymes,” he says. It’s a page from the Steve Jobs playbook; get them hooked on the MADzyme platform, down the line sell them personal hardware.

The power of the system is its “ability to recognize that correlations occur between gender and professions,” says Kathryn Hume. “The downside is that there’s no intentionality behind the system—it’s just math picking up on correlations. It doesn’t know this is a sensitive issue.” There’s a tension between the futuristic and the archaic at play in this technology. AI is evolving much more rapidly than the data it has to work with, so it’s destined not just to reflect and replicate biases but also to prolong and reinforce them.

And sometimes, even when ample data exists, those who build the training sets don’t take deliberate measures to ensure its diversity

But not everyone will be equally represented in that data.

Accordingly, groups that have been the target of systemic discrimination by institutions that include police forces and courts don’t fare any better when judgment is handed over to a machine.

A growing field of research, in fact, now looks to apply algorithmic solutions to the problems of algorithmic bias.

Still, algorithmic interventions only do so much; addressing bias also demands diversity in the programmers who are training machines in the first place.

A growing awareness of algorithmic bias isn’t only a chance to intervene in our approaches to building AI systems. It’s an opportunity to interrogate why the data we’ve created looks like this and what prejudices continue to shape a society that allows these patterns in the data to emerge.

Of course, there’s another solution, elegant in its simplicity and fundamentally fair: get better data.