If you’re interested in machine learning, or, and especially if you have any involvement in big data, analytics, and related matters, before today is over you must read “Why scientific findings by AI can’t always be trusted,” (Maria Temming, Science News, Vol. 195, No. 7, 4/13/2019).
It describes research by Genevera Allen, a data scientist at Rice University, that attempts to answer a question asked in this space not long ago: With neural networks, which can’t explain their logic when presenting a conclusion, aren’t we just substituting trusting a machine’s guts for our own?
Allen’s conclusion: Yes, we are, and no, we shouldn’t.
Machine learning can, she says, be useful for providing preliminary results humans can later validate. “More exploratory algorithms that poke around datasets to find previously unknown patterns or relationships are very hard to verify,” she explains. “Deferring judgment to such autonomous systems may lead to faulty conclusions.”
Reinforcing the parallel with humans and their guts, Allen points out one of the more important limitations of machine learning: “… data-mining algorithms are designed to draw conclusions with no uncertainty.”
The people I know who trust their guts also seem to lack uncertainty.
Among those who should be less certain are those who figure the so-called “technological singularity” represents the biggest risk AI poses to humanity at large. The singularity — runaway AI where automated improvement cycles beget ever-more-advanced non-biological superintelligences — is the least of our concerns, for the simple reason that intelligence and motivation have little to do with each other.
To choose a banal example, Watson beat all human opponents at Jeopardy. We didn’t see a bunch of autonomous Watsons vying to become the next game-show contestants. Watson provided the ability; IBM’s researchers provided the motivation.
If we shouldn’t worry about the Singularity, what should concern us?
And is so often the case, the danger doesn’t come from the technology itself. It comes from us pesky human beings who will, inevitably, use it for nefarious purposes.
This isn’t science fiction. The risk is now. Assuming you haven’t been living in a cave the past couple of years you know that Russian operatives deployed thousands of ‘bots across social media to influence the 2016 election by creating a Twitter echo chamber for opinions they wanted spread to audiences they considered vulnerable.
Now … add sophisticated text generation to these ‘bots capabilities.
You thought Photoshop was dangerous? Take it a step further: We already have the technology to convincingly CGI the faces of dead people onto living actors. What’s to stop a political campaign from using this technology to make it appear that their opponent gave a speech encouraging everyone to, say, embrace Satan as their lord and master?
Oh, and, by the way, as one of those who is or soon will be responsible for making your company more Digital,” it likely won’t be long before you find yourself figuring out whether, in this brave new world, it is more blessed to give than to receive. Because while less politically alarming, do you doubt your Marketing Department won’t want to be the last one on their block to have these new toys to play with?
The same technologies our geopolitical opponents have and will use to sell us their preferred candidates for office will undoubtedly help marketeers everywhere sell us their products and services.
How to solve this?
It’s quite certain prevention isn’t an option, although, as advocated in this space once or twice, we might hope for legislation restricting first amendment rights to actual human persons and not their technological agents, and, beyond that, explicitly limiting the subjects non-humans are allowed to speak about while also requiring all non-human messagers to clearly identify themselves as such.
We might also hope that, unlike the currently pitiful enforcement of the Do-Not-Call Implementation Act of 2003, enforcement of the Shut the ‘Bots Up Act of 2019 would be more vigorous.
Don’t hold your breath.
What might help at least a bit would be development of AI defenses for AI offenses.
Way back in 1997 I proposed that some independent authority should establish a Trusted Information Provider (TIP) certification that information consumers could use to decide which sources to rely on.
What we need now is like that, only using the same amplification techniques the bad guys are using. We need something a lot like spam filters and malware protection — products that use AI techniques to identify and warn users about ‘bot-authored content.
Of course, we’d then need some way to distinguish legitimate ‘bot-blocking software from phony alternatives.
Think of it as full employment for epistemologists.