Explainer
AI
Belief
Creed
5 min read

Whether it's AI or us, it's OK to be ignorant

Our search for answers begins by recognising that we don’t have them.

Simon Walters is Curate at Holy Trinity Huddersfield.

A street sticker displays multiple lines reading 'and then?'
Stephen Harlan on Unsplash.

When was the last time you admitted you didn’t know something? I don’t say it as much as I ought to. I’ve certainly felt the consequences of admitting ignorance – of being ridiculed for being entirely unaware of a pop culture reference, of being found out that I wasn’t paying as close attention to what my partner was saying as she expected. In a hyper-connected age when the wealth of human knowledge is at our fingertips, ignorance can hardly be viewed as a virtue. 

A recent study on the development of artificial intelligence holds out more hope for the value of admitting our ignorance than we might have previously imagined. Despite wide-spread hype and fearmongering about the perils of AI, our current models are in many ways developed in similar ways to how an animal is trained. An AI system such as ChatGPT might have access to unimaginable amounts of information, but it requires training by humans on what information is valuable or not, whether it has appropriately understood the request it has received, and whether its answer is correct. The idea is that human feedback helps the AI to hone its model through positive feedback for correct answers, and negative feedback for incorrect answers, so that it keeps whatever method led to positive feedback and changes whatever method led to negative feedback. It really isn’t that far away from how animals are trained. 

However, a problem has emerged. AI systems have become adept at giving coherent and convincing sounding answers that are entirely incorrect. How has this happened? 

This is a tool; it is good at some tasks, and less good at others. And, like all tools, it does not have an intrinsic morality. 

In digging into the training method for AI, the researchers found that the humans training the AI flagged answers of “I don’t know” as unsatisfactory. On one level this makes sense. The whole purpose of these systems is to provide answers, after all. But rather than causing the AI to return and rethink its data, it instead developed increasingly convincing answers that were not true whatsoever, to the point where the human supervisors didn’t flag sufficiently convincing answers as wrong because they themselves didn’t realise that they were wrong. The result is that “the more difficult the question and the more advanced model you use, the more likely you are to get well-packaged, plausible nonsense as your answer.” 

Uncovering some of what is going on in AI systems dispels both the fervent hype that artificial intelligence might be our saviour, and the deep fear that it might be our societal downfall. This is a tool; it is good at some tasks, and less good at others. And, like all tools, it does not have an intrinsic morality. Whether it is used for good or ill depends on the approach of the humans that use it. 

But this study also uncovers our strained relationship with ignorance. Problems arise in the answers given by systems like ChatGPT because a convincing answer is valued more than admitting ignorance, even if the convincing answer is not at all correct. Because the AI has been trained to avoid admitting it doesn’t know something, all of its answers are less reliable, even the ones that are actually correct.  

This is not a problem limited to artificial intelligence. I had a friend who seemed incapable of admitting that he didn’t know something, and whenever he was corrected by someone else, he would make it sound like his first answer was actually the correct one, rather than whatever he had said. I don’t know how aware he was that he did this, but the result was that I didn’t particularly trust whatever he said to be correct. Paradoxically, had he admitted his ignorance more readily, I would have believed him to be less ignorant. 

It is strange that admitting ignorance is so avoided. After all, it is in many ways our default state. No one faults a baby or a child for not knowing things. If anything, we expect ignorance to be a fuel for curiosity. Our search for answers begins in the recognition that we don’t have them. And in an age where approximately 500 hours of video is uploaded to YouTube every minute, the sum of what we don’t know must by necessity be vastly greater than all that we do know. What any one of us can know is only a small fraction of all there is to know. 

Crucially, admitting we do not know everything is not the same as saying that we do not know anything

One of the gifts of Christian theology is an ability to recognize what it is that makes us human. One of these things is the fact that any created thing is, by definition, limited. God alone is the only one who can be described by the ‘omnis’. He is omnipotent, omnipresent, and omniscient. There is no limit to his power, and presence, and knowledge. The distinction between creator and creation means that created things have limits to their power, presence, and knowledge. We cannot do whatever we want. We cannot be everywhere at the same time. And we cannot know everything there is to be known.  

Projecting infinite knowledge is essentially claiming to be God. Admitting our ignorance is therefore merely recognizing our nature as created beings, acknowledging to one another that we are not God and therefore cannot know everything. But, crucially, admitting we do not know everything is not the same as saying that we do not know anything. Our God-given nature is one of discovery and learning. I sometimes like to imagine God’s delight in our discovery of some previously unknown facet of his creation, as he gets to share with us in all that he has made. Perhaps what really matters is what we do with our ignorance. Will we simply remain satisfied not to know, or will it turn us outwards to delight in the new things that lie behind every corner? 

For the developers of ChatGPT and the like, there is also a reminder here that we ought not to expect AI to take on the attributes of God. AI used well in the hands of humans may yet do extraordinary things for us, but it will not truly be able to do anything, be everywhere, or know everything. Perhaps if it was trained to say ‘I don’t know’ a little more, we might all learn a little more about the nature of the world God has made. 

Article
AI
Culture
Generosity
Psychology
Virtues
5 min read

AI will never codify the unruly instructions that make us human

The many exceptions to the rules are what make us human.
A desperate man wearing 18th century clothes holds candlesticks
Jean Valjean and the candlesticks, in Les Misérables.

On average, students with surnames beginning in the letters A-E get higher grades than those who come later in the alphabet. Good looking people get more favourable divorce settlements through the courts, and higher payouts for damages. Tall people are more likely to get promoted than their shorter colleagues, and judges give out harsher sentences just before lunch. It is clear that human judgement is problematically biased – sometimes with significant consequences. 

But imagine you were on the receiving end of such treatment, and wanted to appeal your overly harsh sentence, your unfair court settlement or your punitive essay grade: is Artificial Intelligence the answer? Is AI intelligent enough to review the evidence, consider the rules, ignore human vagaries, and issue an impartial, more sophisticated outcome?  

In many cases, the short answer is yes. Conveniently, AI can review 50 CVs, conduct 50 “chatbot” style interviews, and identify which candidates best fit the criteria for promotion. But is the short and convenient answer always what we want? In their recent publication, As If Human: Ethics and Artificial Intelligence, Nigel Shadbolt and Roger Hampson discuss research which shows that, if wrongly condemned to be shot by a military court but given one last appeal, most people would prefer to appeal in person to a human judge than have the facts of their case reviewed by an AI computer. Likewise, terminally ill patients indicate a preference for doctor’s opinions over computer calculations on when to withdraw life sustaining treatment, even though a computer has a higher predictive power to judge when someone’s life might be coming to an end. This preference may seem counterintuitive, but apparently the cold impartiality—and at times, the impenetrability—of machine logic might work for promotions, but fails to satisfy the desire for human dignity when it comes to matters of life and death.  

In addition, Shadbolt and Hampson make the point that AI is actually much less intelligent than many of us tend to think. An AI machine can be instructed to apply certain rules to decision making and can apply those rules even in quite complex situations, but the determination of those rules can only happen in one of two ways: either the rules must be invented or predetermined by whoever programmes the machine, or the rules must be observable to a “Large Language Model” AI when it scrapes the internet to observe common and typical aspects of human behaviour.  

The former option, deciding the rules in advance, is by no means straightforward. Humans abide by a complex web of intersecting ethical codes, often slipping seamlessly between utilitarianism (what achieves the most amount of good for the most amount of people?) virtue ethics (what makes me a good person?) and theological or deontological ideas (what does God or wider society expect me to do?) This complexity, as Shadbolt and Hampson observe, means that: 

“Contemporary intellectual discourse has not even the beginnings of an agreed universal basis for notions of good and evil, or right and wrong.”  

The solution might be option two – to ask AI to do a data scrape of human behaviour and use its superior processing power to determine if there actually is some sort of universal basis to our ethical codes, perhaps one that humanity hasn’t noticed yet. For example, you might instruct a large language model AI to find 1,000,000 instances of a particular pro-social act, such as generous giving, and from that to determine a universal set of rules for what counts as generosity. This is an experiment that has not yet been done, probably because it is unlikely to yield satisfactory results. After all, what is real generosity? Isn’t the truly generous person one who makes a generous gesture even when it is not socially appropriate to do so? The rule of real generosity is that it breaks the rules.  

Generosity is not the only human virtue which defies being codified – mercy falls at exactly the same hurdle. AI can never learn to be merciful, because showing mercy involves breaking a rule without having a different rule or sufficient cause to tell it to do so. Stealing is wrong, this is a rule we almost all learn from childhood. But in the famous opening to Les Misérables, Jean Valjean, a destitute convict, steals some silverware from Bishop Myriel who has provided him with hospitality. Valjean is soon caught by the police and faces a lifetime of imprisonment and forced labour for his crime. Yet the Bishop shows him mercy, falsely informing the police that the silverware was a gift and even adding two further candlesticks to the swag. Stealing is, objectively, still wrong, but the rule is temporarily suspended, or superseded, by the bishop’s wholly unruly act of mercy.   

Teaching his followers one day, Jesus stunned the crowd with a catalogue of unruly instructions. He said, “Give to everyone who asks of you,” and “Love your enemies” and “Do good to those who hate you.” The Gospel writers record that the crowd were amazed, astonished, even panicked! These were rules that challenged many assumptions about the “right” way to live – many of the social and religious “rules” of the day. And Jesus modelled this unruly way of life too – actively healing people on the designated day of rest, dining with social outcasts and having contact with those who had “unclean” illnesses such as leprosy. Overall, the message of Jesus was loud and clear, people matter more than rules.  

AI will never understand this, because to an AI people don’t actually exist, only rules exist. Rules can be programmed in manually or extracted from a data scrape, and one rule can be superseded by another rule, but beyond that a rule can never just be illogically or irrationally broken by a machine. Put more simply, AI can show us in a simplistic way what fairness ought to look like and can protect a judge from being punitive just because they are a bit hungry. There are many positive applications to the use of AI in overcoming humanity’s unconscious and illogical biases. But at the end of the day, only a human can look Jean Valjean in the eye and say, “Here, take these candlesticks too.”   

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