artificial intelligence

Reflective Equilibrium in a Turbulent Lake: AI Generated Art and The Future of Artists

Stable diffusion image, prompt: "Reflective equilibrium in a turbulent lake. Painting by Greg Rutkowski" by Anders Sandberg – Future of Humanity Institute, University of Oxford

Is there a future for humans in art? Over the last few weeks the question has been loudly debated online, as machine learning did a surprise charge into making pictures. One image won a state art fair. But artists complain that the AI art is actually a rehash of their art, a form of automated plagiarism that threatens their livelihood.

How do we ethically navigate the turbulent waters of human and machine creativity, business demands, and rapid technological change? Is it even possible?

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AI and the Transition Paradox

by Aksel Braanen Sterri

The most important development in human history will take place not too far in the future. Artificial intelligence, or AI for short, will become better (and cheaper) than humans at most tasks. This will generate enormous wealth that can be used to fill human needs.

However, since most humans will not be able to compete with AI, there will be little demand for ordinary people’s labour-power. The immediate effect of a world without work is that people will lose their primary source of income and whatever meaning, mastery, sense of belonging and status they get from their work. Our collective challenge is to find meaning and other ways to reliably get what we need in this new world.

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Hedonism, the Experience Machine, and Virtual Reality

By Roger Crisp

I take hedonism about well-being or welfare to be the view that the only thing that is good for any being is pleasure, and that what makes pleasure good is nothing other than its being pleasant. The standard objections to hedonism of this kind have mostly been of the same form: there are things other than pleasure that are good, and pleasantness isn’t the only property that makes things good. Continue reading

Judgebot.exe Has Encountered a Problem and Can No Longer Serve

Written by Stephen Rainey

Artificial intelligence (AI) is anticipated by many as having the potential to revolutionise traditional fields of knowledge and expertise. In some quarters, this has led to fears about the future of work, with machines muscling in on otherwise human work. Elon Musk is rattling cages again in this context with his imaginary ‘Teslabot’. Reports on the future of work have included these replacement fears for administrative jobs, service and care roles, manufacturing, medical imaging, and the law.

In the context of legal decision-making, a job well done includes reference to prior cases as well as statute. This is, in part, to ensure continuity and consistency in legal decision-making. The more that relevant cases can be drawn upon in any instance of legal decision-making, the better the possibility of good decision-making. But given the volume of legal documentation and the passage of time, there may be too much for legal practitioners to fully comprehend.

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A Sad Victory

I recently watched the documentary AlphaGo, directed by Greg Kohs. The film tells the story of the refinement of AlphaGo—a computer Go program built by DeepMind—and tracks the match between AlphaGo and 18-time world champion in Go Lee Sedol.

Go is an ancient Chinese board game. It was considered one of the four essential arts of aristocratic Chinese scholars. The goal is to end the game having captured more territory than your opponent. What makes Go a particularly interesting game for AI to master is, first, its complexity. Compared to chess, Go has a larger board, and many more alternatives to consider per move. The number of possible moves in a given position is about 20 in chess; in Go, it’s about 200. The number of possible configurations of the board is more than the number of atoms in the universe. Second, Go is a game in which intuition is believed to play a big role. When professionals get asked why they played a particular move, they will often respond something to the effect that ‘it felt right’. It is this intuitive quality why Go is sometimes considered an art, and Go players artists. For a computer program to beat human Go players, then, it would have to mimic human intuition (or, more precisely, mimic the results of human intuition).

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Should PREDICTED Smokers Get Transplants?

By Tom Douglas

Jack has smoked a packet a day since he was 22. Now, at 52, he needs a heart and lung transplant.

Should he be refused a transplant to allow a non-smoker with a similar medical need to receive one? More generally: does his history of smoking reduce his claim to scarce medical resources?

If it does, then what should we say about Jill, who has never touched a cigarette, but is predicted to become a smoker in the future? Perhaps Jill is 20 years old and from an ethnic group with very high rates of smoking uptake in their 20s. Or perhaps a machine-learning tool has analysed her past facebook posts and google searches and identified her as a ‘high risk’ for taking up smoking—she has an appetite for risk, an unusual susceptibility to peer pressure, and a large number of smokers among her friends. Should Jill’s predicted smoking count against her, were she to need a transplant? Intuitively, it shouldn’t. But why not?

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Video Series: Is AI Racist? Can We Trust it? Interview with Prof. Colin Gavaghan

Should self-driving cars be programmed in a way that always protects ‘the driver’? Who is responsible if an AI makes a mistake? Will AI used in policing be less racially biased than police officers? Should a human being always take the final decision? Will we become too reliant on AIs and lose important skills? Many interesting questions answered in this video interview with Dr Katrien Devolder.

Oxford Uehiro Prize in Practical Ethics: Should We Take Moral Advice From Our Computers? written by Mahmoud Ghanem

This essay received an Honourable Mention in the undergraduate category of the Oxford Uehiro Prize in Practical Ethics.

Written by University of Oxford student, Mahmoud Ghanem

The Case For Computer Assisted Ethics

In the interest of rigour, I will avoid use of the phrase “Artificial Intelligence”, though many of the techniques I will discuss, namely statistical inference and automated theorem proving underpin most of what is described as “AI” today.

Whether we believe that the goal of moral actions ought to be to form good habits, to maximise some quality in the world, to follow the example of certain role models, or to adhere to some set of rules or guiding principles, a good case for consulting a well designed computer program in the process of making our moral decisions can be made. After all, the process of carrying out each of the above successfully at least requires:

(1) Access to relevant and accurate data, and

(2) The ability to draw accurate conclusions by analysing such data.

Both of which are things that computers are very good at. Continue reading

Video Series: Walter Sinnott-Armstrong on Moral Artificial Intelligence

Professor Walter Sinnott-Armstrong (Duke University and Oxford Martin Visiting Fellow) plans to develop a computer system (and a phone app) that will help us gain knowledge about human moral judgment and that will make moral judgment better. But will this moral AI make us morally lazy? Will it be abused? Could this moral AI take over the world? Professor Armstrong explains…

Guest Post: ENHANCING WISDOM

Written by Darlei Dall’Agnol[1]

 

stephen hawking

 

 

 

Stephen Hawking has recently made two very strong declarations:

  • Philosophy is dead;
  • Artificial intelligence could spell the end of the human race.

I wonder whether there is a close connection between the two. In fact, I believe that the second will be true only if the first is. But philosophy is not dead and it may undoubtedly help us to prevent the catastrophic consequences of misusing science and technology. Thus, I will argue that it is through the enhancement of our wisdom that we can hope to avoid artificial intelligence (AI) causing the end of mankind.  Continue reading

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