AI debates both sides of the dangers of artificial intelligence to the human race

By Donna Lu

An artificial intelligence has debated the dangers of AI – narrowly convincing audience members that the technology will do more good than harm.

Project Debater, a robot developed by IBM, spoke on both sides of the argument, with two human teammates for each side helping it out. Talking in a female American voice to a crowd at the University of Cambridge Union on Thursday evening, the AI gave each side’s opening statements, using arguments drawn from more than 1100 human submissions made ahead of time.

On the proposition side, arguing that AI will bring more harm than good, Project Debater’s opening remarks were darkly ironic. “AI can cause a lot of harm,” it said. “AI will not be able to make a decision that is the morally correct one, because morality is unique to humans.”

“AI companies still have too little expertise on how to properly assess datasets and filter out bias,” it added. “AI will take human bias and will fixate it for generations.”

The AI used an application known as “speech by crowd” to generate its arguments, analysing submissions people had sent in online. Project Debater then sorted these into key themes, as well as identifying redundancy – submissions making the same point using different words.

The AI argued coherently but had a few slip-ups. Sometimes it repeated itself – while talking about the ability of AI to perform mundane and repetitive tasks, for example – and it didn’t provide detailed examples to support its claims.

While debating on the opposition side, which was advocating for the overall benefits of AI, Project Debater argued that AI would create new jobs in certain sectors and “bring a lot more efficiency to the workplace”.

But then it made a point that was counter to its argument: “AI capabilities caring for patients or robots teaching schoolchildren – there is no longer a demand for humans in those fields either.”

The pro-AI side narrowly won, gaining 51.22 per cent of the audience vote.

Project Debater argued with humans for the first time last year, and in February this year lost in a one-on-one against champion debater Harish Natarajan, who also spoke at Cambridge as the third speaker for the team arguing in favour of AI.

IBM has plans to use the speech-by-crowd AI as a tool for collecting feedback from large numbers of people. For instance, it could be used by governments seeking public opinions about policies or by companies wanting input from employees, said IBM engineer Noam Slonim.

“This technology can help to establish an interesting and effective communication channel between the decision maker and the people that are going to be impacted by the decision,” he said.

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New advances in quantum artificial intelligence could lead to super-smart machines

by Bryan Nelson

Quantum physics has some spooky, anti-intuitive effects, but it could also be essential to how actual intuition works, at least in regards to artificial intelligence.

In a new study, researcher Vedran Dunjko and co-authors applied a quantum analysis to a field within artificial intelligence called reinforcement learning, which deals with how to program a machine to make appropriate choices to maximize a cumulative reward. The field is surprisingly complex and must take into account everything from game theory to information theory.

Dunjko and his team found that quantum effects, when applied to reinforcement learning in artificial intelligence systems, could provide quadratic improvements in learning efficiency, reports Exponential improvements might even be possible over short-term performance tasks. The study was published in the journal Physical Review Letters.

“This is, to our knowledge, the first work which shows that quantum improvements are possible in more general, interactive learning tasks,” explained Dunjko. “Thus, it opens up a new frontier of research in quantum machine learning.”

One of the key quantum effects in regards to learning is quantum superposition, which potentially allows a machine to perform many steps simultaneously. Such a system has vastly improved processing power, which allows it to compute more variables when making decisions.

The research is tantalizing, in part because it mirrors some theories about how biological brains might produce higher cognitive states, possibly even being related to consciousness. For instance, some scientists have proposed the idea that our brains pull off their complex calculations by making use of quantum computation.

Could quantum effects unlock consciousness in our machines? Quantum physics isn’t likely to produce HAL from “2001: A Space Odyssey” right away; the most immediate improvements in artificial intelligence will likely come in complex fields such as climate modeling or automated cars. But eventually, who knows?

You probably won’t want to be taking a joyride in an automated vehicle the moment it becomes conscious, if HAL is an example of what to expect.

“While the initial results are very encouraging, we have only begun to investigate the potential of quantum machine learning,” said Dunjko. “We plan on furthering our understanding of how quantum effects can aid in aspects of machine learning in an increasingly more general learning setting. One of the open questions we are interested in is whether quantum effects can play an instrumental role in the design of true artificial intelligence.”