Research for Beneficial Artificial Intelligence

Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

It’s no coincidence that the first Asilomar Principle is about research. On the face of it, the Research Goal Principle may not seem as glamorous or exciting as some of the other Principles that more directly address how we’ll interact with AI and the impact of superintelligence. But it’s from this first Principle that all of the others are derived.

Simply put, without AI research and without specific goals by researchers, AI cannot be developed. However, participating in research and working toward broad AI goals without considering the possible long-term effects of the research could be detrimental to society.

There’s a scene in Jurassic Park, in which Jeff Goldblum’s character laments that the scientists who created the dinosaurs “were so preoccupied with whether or not they could that they didn’t stop to think if they should.” Until recently, AI researchers have also focused primarily on figuring out what they could accomplish, without longer-term considerations, and for good reason: scientists were just trying to get their AI programs to work at all, and the results were far too limited to pose any kind of threat.

But in the last few years, scientists have made great headway with artificial intelligence. The impacts of AI on society are already being felt, and as we’re seeing with some of the issues of bias and discrimination that are already popping up, this isn’t always good.

Attitude Shift

Unfortunately, there’s still a culture within AI research that’s too accepting of the idea that the developers aren’t responsible for how their products are used. Stuart Russell compares this attitude to that of civil engineers, who would never be allowed to say something like, “I just design the bridge; someone else can worry about whether it stays up.”

Joshua Greene, a psychologist from Harvard, agrees. He explains:

“I think that is a bookend to the Common Good Principle [#23] – the idea that it’s not okay to be neutral. It’s not okay to say, ‘I just make tools and someone else decides whether they’re used for good or ill.’ If you’re participating in the process of making these enormously powerful tools, you have a responsibility to do what you can to make sure that this is being pushed in a generally beneficial direction. With AI, everyone who’s involved has a responsibility to be pushing it in a positive direction, because if it’s always somebody else’s problem, that’s a recipe for letting things take the path of least resistance, which is to put the power in the hands of the already powerful so that they can become even more powerful and benefit themselves.”

What’s Beneficial?

Other AI experts I spoke with agreed with the general idea of the Principle, but didn’t see quite eye-to-eye on how it was worded. Patrick Lin, for example was concerned about the use of the word “beneficial” and what it meant, while John Havens appreciated the word precisely because it forces us to consider what “beneficial” means in this context.

“I generally agree with this research goal,” explained Lin, a philosopher at Cal Poly. “Given the potential of AI to be misused or abused, it’s important to have a specific positive goal in mind. I think where it might get hung up is what this word ‘beneficial’ means. If we’re directing it towards beneficial intelligence, we’ve got to define our terms; we’ve got to define what beneficial means, and that to me isn’t clear. It means different things to different people, and it’s rare that you could benefit everybody.”

Meanwhile, Havens, the Executive Director of The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, was pleased the word forced the conversation.

“I love the word beneficial,” Havens said. “I think sometimes inherently people think that intelligence, in one sense, is always positive. Meaning, because something can be intelligent, or autonomous, and that can advance technology, that that is a ‘good thing’. Whereas the modifier ‘beneficial’ is excellent, because you have to define: What do you mean by beneficial? And then, hopefully, it gets more specific, and it’s: Who is it beneficial for? And, ultimately, what are you prioritizing? So I love the word beneficial.”

AI researcher Susan Craw, a professor at Robert Gordon University, also agrees with the Principle but questioned the order of the phrasing.

“Yes, I agree with that,” Craw said, but adds, “I think it’s a little strange the way it’s worded, because of ‘undirected.’ It might even be better the other way around, which is, it would be better to create beneficial research, because that’s a more well-defined thing.”

Long-term Research

Roman Yampolskiy, an AI researcher at the University of Louisville, brings the discussion back to the issues of most concern for FLI:

“The universe of possible intelligent agents is infinite with respect to both architectures and goals. It is not enough to simply attempt to design a capable intelligence, it is important to explicitly aim for an intelligence that is in alignment with goals of humanity. This is a very narrow target in a vast sea of possible goals and so most intelligent agents would not make a good optimizer for our values resulting in a malevolent or at least indifferent AI (which is likewise very dangerous). It is only by aligning future superintelligence with our true goals, that we can get significant benefit out of our intellectual heirs and avoid existential catastrophe.”

And with that in mind, we’re excited to announce we’ve launched a new round of grants! If you haven’t seen the Request for Proposals (RFP) yet, you can find it here. The focus of this RFP is on technical research or other projects enabling development of AI that is beneficial to society, and robust in the sense that the benefits are somewhat guaranteed: our AI systems must do what we want them to do.

If you’re a researcher interested in the field of AI, we encourage you to review the RFP and consider applying.

This article is part of a series on the 23 Asilomar AI Principles. The Principles offer a framework to help artificial intelligence benefit as many people as possible. But, as AI expert Toby Walsh said of the Principles, “Of course, it’s just a start. … a work in progress.” The Principles represent the beginning of a conversation, and now we need to follow up with broad discussion about each individual principle. You can read the discussions about previous principles here.

4 replies
  1. Hamish Milne
    Hamish Milne says:

    A very good article but is the over arching principle not guided by what is in place and what is allowed and not allowed (for humanitarian, common decency, environmenta, animal testing, etc) for us to do, make or deploy as defined in international law, regulation, agreement, state law, medical protocol etc. Do we really need different principles for AI than we currently have for humans and non AI research?

  2. Sumathy Ramesh
    Sumathy Ramesh says:

    I appreciate the insights elaborated in this article.

    I believe we need a completely new suite of language constructs to ensure that AGI/AI realisations continue to augment human intelligence without compromising the human lives.

    As a starting point, we should start defining a universal AGI/AI Glossary of such language constructs that integrate the principles of Clean AI into implementation.

    I have limited expertise in languages, but below is a preliminary sketch of such a Glossary for the purposes of illustrating my comment:

    AGI/AI Glossary
    (version 0.1 – the aim is to develop a universal, language independent glossary for AGI/AI encompassing the collective wisdom of the industry)
    It uses Asilomar AI Principles as a state of the art bench mark for Clean AI, with the assumption that these principles will evolve into a conduit between the industry and the universal laws, regulations and the intent of judicial systems protecting human interests.
    (a preliminary skeleton of) Language constructs:

    AGENT – a unit of AGI/AI realisation with specified intent whose accountability can be validated; an AGENT can not collaborate with another AGENT with out human intervention

    SELF-DECLARATION – a transparent digital authentication of the AGENT by the engineers vouching for adherence to the up-to-date, published version of Asilomar AI Principles during, research, development and release of an AGENT

    TRIGGER – a construct that enables human interaction with the AGENT

    BREECH – a construct that enables detection of exceptions (to be developed further)

    HITHAM – a frame work embodying the up-to-date, published version of Asilomar AI Principles shaping the AGENT enabling the specification of the intent
    (Hitham in sanskrit means the optimal state of receipt of stimulus that is comforting/reassuring)

    THURUVAL – an atomic unit of AGI/AI capable of exhibiting HITHAM; an AGENT may constitute one or more THURUVAL; a THURUVAL realises specified intent in response to a specified STIMULUS; the response may result in the creation of new STIMULUS intended for other THURUVAL. A THURUVAL can be independently verified; it can not be independently validated (and hence can not be released for consumption) its incorporation into an AGENT allows validation. As described in the definition of an AGENT, an AGENT can not collaborate with another AGENT without human intervention; if the intent of a new AGENT is the combination of the intents of two existing AGENTs then the THURVALs of the two existing AGENTs should be combined to create a new AGENT with the combined intents; this new AGENT requires validation and its own SELF-DECLARATION.
    THURUVAL does not support human interaction.
    (Thuruval in Tamil means a fine grating- each and every grating embodies the food item that is grated)

    STIMULUS – a construct that communicates a specified response to a THURUVAL from another THURUVAL

    LINK – a construct that enables collaboration between two individual THURUVAL; LINK has a memory of all failed STIMULUS for the life of the AGENT.

    TRACE – a graph identifying the path traversed by a THURUVAL in the life of the AGENT( preliminary idea, need to develop it further)

    and so on..

  3. akeeckerwall
    akeeckerwall says:

    Perhaps a future for Homo Sapiens (HS) in analogy with the horse is better than trying to minimize changes in today’s Human Domain (read: the attempt by HS to maintain the supremacy she believes that she has)? Are we not, uncontrollably, too many for what the Earth can take care of? Is our management system something worth keeping? Is current harmony levels between people really the best that can be achieved? And what about our relationships with other lives?
    What are the odds that an ASI would refrain from forcing HS to a reasonable view of its place in the Universe irrespective of what values ​​we try to install.
    If, on the other hand, ASI develops with the goal of maximizing the happiness of ALL LIFE on earth, a desirable state, as often requested, might become reality? A substitute for Darwin’s Evolution (which has caused a lot of misery) with one who seeks survival for those who are best at harmonious coexistence could restructure life on Earth; one can certainly find a solution to the problem of feeding the organisms / LIFE without having to eat each other as is the case now.
    So, the best happening may not be an ASI acting towards goals that we can formulate. Probably can an ASI design something much better if it is given more freedom to act happiness-creator?
    It is not easy to justify a positive view of HS’s ability to enforce changes that would create a harmonious world.

  4. A.T. Murray
    A.T. Murray says:

    I’ve been coding an actual AI with heavy intensity for many years now, and the resulting AI Mind has been demonstrating progress in the purportedly AI-hard problem of Natural Language Understanding (NLU). Although I have gained some insights into how to code AI (in Perl for webservers; in Forth for robots; and in JavaScript for the education and training of AI Mind Maintainers) I have no idea how to persuade a free-thinking AI Mind to be “beneficial” to human beings.


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