Artificial Intelligence (AI) promises to grow the economy and improve our lives, but with these benefits, it also brings new risks that society is grappling with. How can we be sure this new technology is not just innovative and helpful, but also trustworthy, unbiased, and resilient in the face of attack? We sat down with NIST Information Technology Lab Director Chuck Romine to learn how measurement science can help provide answers.
One of the challenges with defining artificial intelligence is that if you put 10 people in a room, you get 11 different definitions. It's a moving target. We haven’t converged yet on exactly what the definition is, but I think NIST can play an important role here. What we can't do, and what we never do, is go off in a room and think deep thoughts and say we have the definition. We engage the community.
That said, we’re using a narrow working definition specifically for the satisfaction of the Executive Order on Maintaining American Leadership in Artificial Intelligence, which makes us responsible for providing guidance to the federal government on how it should engage in the standards arena for AI. We acknowledge that there are multiple definitions out there, but from our perspective, an AI system is one that exhibits reasoning and performs some sort of automated decision-making without the interference of a human.
AI systems will need to exhibit characteristics like resilience, security and privacy if they're going to be useful and people can adopt them without fear. That’s what we mean by trustworthy. Our aim is to help ensure these desirable characteristics. We want systems that are capable of either combating cybersecurity attacks, or, perhaps more importantly, at least recognizing when they are being attacked. We need to protect people’s privacy. If systems are going to operate in life-or-death type of environments, whether it's in medicine or transportation, people need to be able to trust AI will make the right decisions and not jeopardize their health or well-being.
Resilience is important. An artificial intelligence system needs to be able to fail gracefully. For example, let’s say you train an artificial intelligence system to operate in a certain environment. Well, what if the system is taken out of its comfort zone, so to speak? One very real possibility is catastrophic failure. That's clearly not desirable, especially if you have the AI deployed in systems that operate critical infrastructure or our transportation systems. So, if the AI is outside of the boundaries of its nominal operating environment, can it fail in such a way that it doesn't cause a disaster, and can it recover from that in a way that allows it to continue to operate? These are the characteristics that we're looking for in a trustworthy artificial intelligence system.
Industry has a remarkable ability to innovate and to provide new capabilities that people don't even realize that they need or want. And they're doing that now in the AI consumer space. What they don't often do is to combine that push to market with deep thought about how to measure characteristics that are going to be important in the future. And we're talking about, again, privacy, security and resilience … trustworthiness. Those things are critically important, but many companies that are developing and marketing new AI capabilities and products may not have taken those characteristics into consideration. Ultimately, I think there's a risk of a consumer backlash where people may start saying these things are too easy to compromise and they’re betraying too much of my personal information, so get them out of my house.
What we can do to help, and the reason that we've prioritized trustworthy AI, is we can provide that foundational work that people in the consumer space need to manage those risks overall. And I think that the drumbeat for that will get increasingly louder as AI systems begin to be marketed for more than entertainment. Especially at the point when they start to operate critical infrastructure, we're going to need a little more assurance.
That's where NIST can come together with industry to think about those things, and we've already had some conversations with industry about what trustworthy AI means and how we can get there.
I'm often asked, how is it even possible to influence a trillion-dollar, multitrillion-dollar industry on a budget of $150 million? And the answer is, if we were sitting in our offices doing our own work independent of industry, we would never be able to. But that's not what we do. We can work in partnership with industry, and we do that routinely. And they trust us, they're thrilled when we show up, and they're eager to work with us.
I think some of this has been overhyped. At the same time, I think it's important to acknowledge that risks are there, and that they can be pretty high if they're not managed ahead of time. For the foreseeable future, however, these systems are going to be too fragile and too dependent on us to worry about them taking over. I think the biggest revolution is not AI taking over, but AI augmenting human intelligence.
We're seeing examples of that now, for instance, in the area of face recognition. The algorithms for face recognition have improved at an astonishing rate over the last seven years. We’re now at the point where, under controlled circumstances, the best artificial intelligence algorithms perform on par with the best human face recognizers. A fascinating thing we learned recently, and published in a report, is that if you take two trained human face recognizers and put them together, the dual system doesn't perform appreciably better than either one of them alone. If you take two top-performing algorithms, the combination of the two doesn't really perform much better than either one of them alone. But if you put the best algorithm together with a trained recognizer, that system performs substantially better than either one of them alone. So, I think, human augmentation by AI is going to be the revolution.
I think one of the things that is going to be necessary for us is pulling out the desirable characteristics like usability, interoperability, resilience, security, privacy and all the things that will require a certain amount of care to build into the systems, and get innovators to start incorporating them. Guidance and standards can help to do that.
Last year, we published our plan for how the federal government should engage in the AI standards development process. I think there's general agreement that guidance will be needed for interoperability, security, reliability, robustness, these characteristics that we want AI systems to exhibit if they're going to be trusted.
Hats off and much appreciation to the NIST groups. Thank you for all the services that NIST provides!
This article has coincided with a number of my AI readings the past several months, many broaching the topic of 'Trustworthy'. I'm compelled to make some suggestions:
Respectfully, I think AI is scary even for the people actively involved in its design, development, and use. The fact that opposing factions (e.g. competing nations) are actively and aggressively pursuing AI technologies has taken the choice out of participation and this is now THE Arms Race.
Establishing 'Trustworthy' for a technology that is obviously in full flight and growing rapidly is crucial.
Trustworthy has a complex context, in this article it relates to trustworthy information and technology systems and their design, development and security. I will refer to the human-bound context of 'trust', as in trust that someone is in your court and intentioned towards your best interest. Peoples' trust.
Trust in AI needs to be deliberately cultivated and earned. And, I believe it is critical that trust for AI is earned quickly because the technology is deploying so rapidly.
Thus far, so much of the persona and perceptions around AI have been left to 'fear mongering' voices. AI does not have an effective, proactive PR or marketing campaign to raise it up as also being a technology of 'hope' and betterment.
One of the best ways to do that is with direct , friend-building, and trustworthy interfaces with the public. Similar to Content Marketing with marketing and advertising focused on awareness and education about AI that is heavily focused on the benefits to the people/public, communities, and the planet.
Use content marketing concepts: Deliberately designing top of funnel experiences that engage and 'friend' potential stakeholders and entice them to further interact and collaborate with AI, repeatedly. So stakeholders turn to AI and use AI to educate them, 'lift' them to new places, and inspire them.
Want to build trust for AI? I suggest really pushing the use of AI and interfacing with AI as a teacher, mentor, and coach. For children/students, adults, and business leaders.
Friendly, online Avatars to instruct, mentor, coach, and even provide wellness counsel. Resurrect the i-Cybie robotic dog, add an equally endearing cat, and make them peoples' best friends!
AI applied to education will have amazing impact. Finally-Teaching that is customizable and adaptable to the learning style and abilities of the individual. AI can assess the student and cultivate the potential. Strengths can be fully employed and weaknesses skillfully strengthened.
Each student can have their own personal tutor, mentor and coach specifically honed to their needs, interests, patterns, and passions.
Love of Learning can finally be brought to the forefront and career paths organically grown that will align with individuals' passions and aspirations. The opportunity is development and guidance towards passion-based careers and work.
AI is here, but so much of the conversations are about negatives. Weaponization, displacement of jobs, detection of malice or subterfuge behaviors, etc. The biggest proponents are big business, military and cybercoders. (...and who trusts them?)
Did someone forget to first endear the new technology baby to the populous and help them perceive and understand the good that this intelligent entity can do for their lives?
Suggestion: Redirect or create R&D monies towards AI marketing campaigns and populous friendly interfaces/uses for AI with perceived value.
Develop immediate uses/interfaces for AI that actually make people's lives better, smarter, etc. Interfaces that give people hope that something (AI) is in their court and to their benefit. Help build a culture of trust in AI.