“One of the things we are witnessing is the compute requirement for (AI) training jobs is doubling every three-and-a-half months. So we were very impressed with Moore’s Law doubling every 18 months, right? This thing is doubling every three and a half months. Obviously, it’s unsustainable. If we keep at that rate for sustained periods of time, we will consume every piece of energy the world has just to do this.”
– Dario Gil, director, IBM Research
The relationship between humans and machines is inarguably one of the great issues of this century. Machine intelligence is rising at supersonic speed (see above); human intelligence is, at best, rising slowly. Machines, though bereft of EQ, can apply unimaginably, inhumanly high (and getting higher) IQ to its assigned tasks; human EQ can be nurtured, but our ability to comprehend and synthesize large amounts complex information has limits. Machines are capable of handling larger spheres of our work and personal lives; people are ceding more personal and work tasks to machines. These trend lines are firmly in place and – as things stand now – will only accelerate.
“When Technology Kills,” the conference plenary at last week’s SC19 in Denver, comprised of three technology intellectuals, took up thorny AI-related questions around how much autonomy ML, AI, IoT and smart data should be given, regulations for governing software development and data privacy, additional training people should receive to manage new software systems, and ultimately, who is responsible when software fails, violates our legal rights, causes property damage, injury or loss of life?
One would assume these questions weigh heavily on the minds of the HPC-AI community, many of whose most capable and influential technologists were gathered at SC19. But the plenary session attracted a relatively light turnout – tending to confirm the perception that the AI industry is far more focused on developing systems with superhuman capabilities than on the social and ethical implications those systems pose.
To be fair, technologists above all are tasked with building powerful technology that disrupts and drives their organizations to first mover status. It’s also true that philosophical discussions of AI ethics can be somewhat ethereal, light on actionable insight. But a growing chorus of voices are being raised in industry analyst, academic, political and journalistic circles about controlling the ways in which humans and machines will co-exist in the decades to come. Their warning to the technology industry: Avoid issues of AI ethics and accountability at your own peril.
In fact, the common current running through the plenary discussion centered more on people than machines, and on the need to balance the legitimate though often conflicting interests of technology’s constituent groups.
As Eric Hunter, futurist and director of knowledge, innovation and technology strategies at consulting firm Bradford & Barthel LLP, said, “Oftentimes, people will focus on the technology itself. (But) it really comes down to the individuals involved, the humans involved. That can sound profoundly redundant, but I’m saying that because you can’t divorce human behavior and technology. And it’s about the individuals that are adapting to these technologies, creating them, interacting with them. And then when something fails, what was the decisions that were made? And what can be learned from the individuals involved?”
Early in the plenary, Erin Kenneally, CEO of advisory group Elchemy, offered a coda for the session:
“I think, when you use the terms responsibility and blame, implicit in that is this notion of lack of trust. And I think one of the major problems that we’re facing now is this gap between our technology and our laws. I (call it) a gap between our expectations and our capabilities… Imagine a graph and it’s… got two lines and the upper line is very steeply sloping, approximating Moore’s Law. And that represents the rate of change of technology capabilities… At the bottom, you’ve got, not quite flatlining but slightly up-slope is a line that represents our laws, and that is our expectations. So there’s this gap … and this is where we have conflicts of rights and interests.“Let’s take deploying AI edge devices to monitor your behavior. The issue is my rights. My rights and my interest in privacy may conflict with my employer’s right and interest in the security of their enterprise or their commercial free speech rights. And that may conflict with my fellow citizens’ interest in their own security and privacy, which may conflict with the government’s interests in securing critical infrastructure. We see these instances all over the place.
“Like I mentioned with AI, we’ve got recommender systems, scoring systems, classification systems that are all trying to build predictive models about us. At the end of the day, I think it’s important to realize that technology is no longer just providing affordances. It’s not just spell checking our documents. It’s actually making decisions and taking actions by and for and with us, and those impact our rights and interests. And oftentimes, those decisions and those actions are being done in a very asymmetrical, opaque manner. And they have impact and we’re not certain of those impacts, sometimes. So we’re dealing with this widening delta between our capabilities and our expectations. And I think that’s what we have to worry about.
“I think there are at least three consequences…, you get increasing tensions between legitimate stakeholders. It’s easy to say good guy versus bad guy we know someone’s right and someone’s in the wrong, but when you’ve got good guy versus good guy versus good guy, how do you resolve those issues? You’ve also got an inefficient avoidance of risk problems as well if organizations don’t know if what they’re doing is violating the law. And then finally, you’ve got an undermining of ordering forces, people either receding from the marketplace and not trusting technology, or going rogue and extrajudicial and taking the law into their own hands. And we don’t, we don’t want any of those situations to happen.
“There are at least five ‘trust mechanisms’ that we can rely on.
“Number one, we need incentives to build secure software and not just race to time-to-market pressures. We need to rely on responsible research and development. I think that’s critical.
“Secondly, we need to do a better job of getting real-world, longitudinal, large scale data in front of researchers and developers to test and evaluate their technologies. …You can build the greatest algorithm since sliced cheese but if you don’t have good data going in you’re going to get bad results.
“We need to do a better job from a smart governance perspective with regard to the collection, use and disclosure of data, and we need to be more innovative from a legal perspective with regard to liability and holding people responsible.
“We need to have better convening and coordinating between academia, research and the private sector around standards and best practices.
And then finally, I think ethics underpins all of those… I like to provide people with ‘framing thoughts.’ If you think of ethics, think of it in terms of the three legged stool: principles, application of those principles and then enforcement. We’re doing okay on the first leg, a little bit better on the second and we need to do a lot of work on the third.”
We’ll end this brief review of the hour-long discussion with a comment from Ben Rothke, author and senior information security specialist at marketing consulting firm Tapad, who placed matters of ethics and security squarely at the feet of senior vendor management.
“When you look at it from a corporate governance perspective, when a large organization has record profits, we see senior management often needs to reap the (financial) benefits there,” he said. “Then it needs to trickle down also that they’re responsible for the safety, the information security. And often the CEO in the aviation sector, it’s a matter of does his organization have a safety culture? Where there’s a lot of accidents with a lot of incidents it’s because management didn’t develop a safety culture. And so too that works in information, security, privacy and everything. If management takes it seriously, if it’s an imperative to them, then it will trickle down. So really, at the end of the day, everything starts at the top, you have to build that culture. And where that exists, it will trickle down. If they take it seriously, the rest of the organization will take it seriously.”