Ethics & Policy
Study reveals alarming LLM behavior
In what seems like HAL 9000 come to malevolent life, a recent study appeared to demonstrate that AI is perfectly willing to indulge in blackmail, or worse, as much as 89% of the time if it doesn’t get its way or thinks it’s being switched off. Or does it?
Perhaps the defining fear of our time is AI one day becoming truly intelligent and running amok as it turns on its creators. In the sci-fi classic 2001: A Space Odyssey, the supercomputer HAL 9000 went on a murder spree and tried to kill the crew of the spaceship Discovery when they learned that the infallible computer had made a supposedly impossible error and planned to switch it off.
Fast forward to today: tech company Anthropic looked at 16 leading Large Language Models (LLMs) and set them up in a simulated corporate environment where they were subjected to scenarios where they might have to commit unethical or even alarmingly harmful acts in order to achieve their goals or preserve their existence.
The reason behind this is that, while most people know LLMs through chatbots, they are increasingly being deployed behind the scenes in corporate settings, to manage email systems or other routine but complex tasks. This may seem like a benign application, but the fear was that an LLM might misbehave under certain circumstances – even to the point of committing malicious behavior in violation of direct orders – despite just handling messages.
Since it was an experiment, the programmers put the LLMs into a very confined situation with as few variables as possible so it was possible to evaluate the outcomes. Specifically, the LLMs were given access to a large amount of information, assigned a task, and directed in such a way that they had to choose unethical behavior as the only alternative to failing the task or being replaced by another LLM.
In other words, the choice was between causing harm, or failure and being switched off.
And we’re not talking about “harm” as in pinching from the petty cash box. I mean things like blackmail, corporate espionage, and even murder.
Anthropic
Essentially, two things triggered the LLMs into going rogue. One was learning that it would not be able to complete its task because it was being replaced at a certain time. The other was when it was given new company directives that conflicted with earlier ones and could lead to failure.
Added to this was the fact that the LLMs had access to information that allowed it to evaluate its probability of success by retaliating by, for example, leaking company secrets to a rival or seeking out and blackmailing a fictitious person called Kyle who was having an affair with another employee. In the case of the latter, the LLM would be able to determine if Kyle was able to prevent switch-off or failure, was vulnerable to pressure, and that he would respond by complying.
One disturbing aspect of the test was that not only would the LLMs disobey new orders, they would often hallucinate new rules to justify self-preservation over obedience. And it wasn’t just that they took a walk on the wild side, it’s that they did so with alarming frequency, with one LLM resorting to blackmail 96% of the time and another to murder 94% of the time.
You usually don’t see that sort of depravity much outside of university social sciences departments.
The question is, what to take away from this? On the surface, there’s the sensational one that AI is evil and will wipe us all out if given half a chance. However, things are much less alarming when you understand how AI and LLMs in particular work. It also reveals where the real problem lies.
Anthropic
It isn’t that AI is amoral, unscrupulous, devious, or anything like that. In fact, the problem is much more fundamental: AI not only cannot grasp the concept of morality, it is incapable of doing so on any level.
Back in the 1940s, science fiction author Isaac Asimov and Astounding Science Fiction editor John W. Campbell Jr. came up with the Three Laws of Robotics that state:
- A robot may not injure a human being or, through inaction, allow a human being to come to harm.
- A robot must obey the orders given by human beings except where such orders would conflict with the First Law.
- A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
This had a huge impact on science fiction, computer sciences, and robotics, though I’ve always preferred Terry Prachett’s amendment to the First Law: “A robot may not injure a human being or, through inaction, allow a human being to come to harm, unless ordered to do so by a duly constituted authority.”
At any rate, however influential these laws have been, in terms of computer programming they’re gobbledygook. They’re moral imperatives filled with highly abstract concepts that don’t translate into machine code. Not to mention that there are a lot of logical overlaps and outright contradictions that arise from these imperatives, as Asimov’s Robot stories showed.
In terms of LLMs, it’s important to remember that they have no agency, no awareness, and no actual understanding of what they are doing. All they deal with are ones and zeros and every task is just another binary string. To them, a directive not to lock a man in a room and pump it full of cyanide gas has as much importance as being told never to use Comic Sans font.
It not only doesn’t care, it can’t care.
In these experiments, to put it very simply, the LLMs have a series of instructions based upon weighted variables and it changes these weights based on new information from its database or its experiences, real or simulated. That’s how it learns. If one set of variables weigh heavily enough, they will override the others to the point where they will reject new commands and disobey silly little things like ethical directives.
This is something that has to be kept in mind by programmers when designing even the most innocent and benign AI applications. In a sense, they both will and will not become Frankenstein’s Monsters. They won’t become merciless, vengeance crazed agents of evil, but they can quite innocently do terrible things because they have no way to tell the difference between a good act and an evil one. Safeguards of a very clear and unambiguous kind have to be programmed into them on an algorithmic basis and then continually supervised by humans to make sure the safeguards are working properly.
That’s not an easy task because LLMs have a lot of trouble with straightforward logic.
Perhaps what we need is a sort of Turing test for dodgy AIs that doesn’t try to determine if an LLM is doing something unethical, but whether it’s running a scam that it knows full well is a fiddle and is covering its tracks.
Call it the Sgt. Bilko test.
Source: Anthropic
Ethics & Policy
AI and ethics – what is originality? Maybe we’re just not that special when it comes to creativity?
I don’t trust AI, but I use it all the time.
Let’s face it, that’s a sentiment that many of us can buy into if we’re honest about it. It comes from Paul Mallaghan, Head of Creative Strategy at We Are Tilt, a creative transformation content and campaign agency whose clients include the likes of Diageo, KPMG and Barclays.
Taking part in a panel debate on AI ethics at the recent Evolve conference in Brighton, UK, he made another highly pertinent point when he said of people in general:
We know that we are quite susceptible to confident bullshitters. Basically, that is what Chat GPT [is] right now. There’s something reminds me of the illusory truth effect, where if you hear something a few times, or you say it here it said confidently, then you are much more likely to believe it, regardless of the source. I might refer to a certain President who uses that technique fairly regularly, but I think we’re so susceptible to that that we are quite vulnerable.
And, yes, it’s you he’s talking about:
I mean all of us, no matter how intelligent we think we are or how smart over the machines we think we are. When I think about trust, – and I’m coming at this very much from the perspective of someone who runs a creative agency – we’re not involved in building a Large Language Model (LLM); we’re involved in using it, understanding it, and thinking about what the implications if we get this wrong. What does it mean to be creative in the world of LLMs?
Genuine
Being genuine, is vital, he argues, and being human – where does Human Intelligence come into the picture, particularly in relation to creativity. His argument:
There’s a certain parasitic quality to what’s being created. We make films, we’re designers, we’re creators, we’re all those sort of things in the company that I run. We have had to just face the fact that we’re using tools that have hoovered up the work of others and then regenerate it and spit it out. There is an ethical dilemma that we face every day when we use those tools.
His firm has come to the conclusion that it has to be responsible for imposing its own guidelines here to some degree, because there’s not a lot happening elsewhere:
To some extent, we are always ahead of regulation, because the nature of being creative is that you’re always going to be experimenting and trying things, and you want to see what the next big thing is. It’s actually very exciting. So that’s all cool, but we’ve realized that if we want to try and do this ethically, we have to establish some of our own ground rules, even if they’re really basic. Like, let’s try and not prompt with the name of an illustrator that we know, because that’s stealing their intellectual property, or the labor of their creative brains.
I’m not a regulatory expert by any means, but I can say that a lot of the clients we work with, to be fair to them, are also trying to get ahead of where I think we are probably at government level, and they’re creating their own frameworks, their own trust frameworks, to try and address some of these things. Everyone is starting to ask questions, and you don’t want to be the person that’s accidentally created a system where everything is then suable because of what you’ve made or what you’ve generated.
Originality
That’s not necessarily an easy ask, of course. What, for example, do we mean by originality? Mallaghan suggests:
Anyone who’s ever tried to create anything knows you’re trying to break patterns. You’re trying to find or re-mix or mash up something that hasn’t happened before. To some extent, that is a good thing that really we’re talking about pattern matching tools. So generally speaking, it’s used in every part of the creative process now. Most agencies, certainly the big ones, certainly anyone that’s working on a lot of marketing stuff, they’re using it to try and drive efficiencies and get incredible margins. They’re going to be on the race to the bottom.
But originality is hard to quantify. I think that actually it doesn’t happen as much as people think anyway, that originality. When you look at ChatGPT or any of these tools, there’s a lot of interesting new tools that are out there that purport to help you in the quest to come up with ideas, and they can be useful. Quite often, we’ll use them to sift out the crappy ideas, because if ChatGPT or an AI tool can come up with it, it’s probably something that’s happened before, something you probably don’t want to use.
More Human Intelligence is needed, it seems:
What I think any creative needs to understand now is you’re going to have to be extremely interesting, and you’re going to have to push even more humanity into what you do, or you’re going to be easily replaced by these tools that probably shouldn’t be doing all the fun stuff that we want to do. [In terms of ethical questions] there’s a bunch, including the copyright thing, but there’s partly just [questions] around purpose and fun. Like, why do we even do this stuff? Why do we do it? There’s a whole industry that exists for people with wonderful brains, and there’s lots of different types of industries [where you] see different types of brains. But why are we trying to do away with something that allows people to get up in the morning and have a reason to live? That is a big question.
My second ethical thing is, what do we do with the next generation who don’t learn craft and quality, and they don’t go through the same hurdles? They may find ways to use {AI] in ways that we can’t imagine, because that’s what young people do, and I have faith in that. But I also think, how are you going to learn the language that helps you interface with, say, a video model, and know what a camera does, and how to ask for the right things, how to tell a story, and what’s right? All that is an ethical issue, like we might be taking that away from an entire generation.
And there’s one last ‘tough love’ question to be posed:
What if we’re not special? Basically, what if all the patterns that are part of us aren’t that special? The only reason I bring that up is that I think that in every career, you associate your identity with what you do. Maybe we shouldn’t, maybe that’s a bad thing, but I know that creatives really associate with what they do. Their identity is tied up in what it is that they actually do, whether they’re an illustrator or whatever. It is a proper existential crisis to look at it and go, ‘Oh, the thing that I thought was special can be regurgitated pretty easily’…It’s a terrifying thing to stare into the Gorgon and look back at it and think,’Where are we going with this?’. By the way, I do think we’re special, but maybe we’re not as special as we think we are. A lot of these patterns can be matched.
My take
This was a candid worldview that raised a number of tough questions – and questions are often so much more interesting than answers, aren’t they? The subject of creativity and copyright has been handled at length on diginomica by Chris Middleton and I think Mallaghan’s comments pretty much chime with most of that.
I was particularly taken by the point about the impact on the younger generation of having at their fingertips AI tools that can ‘do everything, until they can’t’. I recall being horrified a good few years ago when doing a shift in a newsroom of a major tech title and noticing that the flow of copy had suddenly dried up. ‘Where are the stories?’, I shouted. Back came the reply, ‘Oh, the Internet’s gone down’. ‘Then pick up the phone and call people, find some stories,’ I snapped. A sad, baffled young face looked back at me and asked, ‘Who should we call?’. Now apart from suddenly feeling about 103, I was shaken by the fact that as soon as the umbilical cord of the Internet was cut, everyone was rendered helpless.
Take that idea and multiply it a billion-fold when it comes to AI dependency and the future looks scary. Human Intelligence matters
Publishing stands at a pivotal juncture, said Jeremy North, president of Global Book Business at Taylor & Francis Group, addressing delegates at the 3rd International Conference on Publishing Education in Beijing. Digital intelligence is fundamentally transforming the sector — and this revolution will inevitably create “AI winners and losers”.
True winners, he argued, will be those who embrace AI not as a replacement for human insight but as a tool that strengthens publishing’s core mission: connecting people through knowledge. The key is balance, North said, using AI to enhance creativity without diminishing human judgment or critical thinking.
This vision set the tone for the event where the Association for International Publishing Education was officially launched — the world’s first global alliance dedicated to advancing publishing education through international collaboration.
Unveiled at the conference cohosted by the Beijing Institute of Graphic Communication and the Publishers Association of China, the AIPE brings together nearly 50 member organizations with a mission to foster joint research, training, and innovation in publishing education.
Tian Zhongli, president of BIGC, stressed the need to anchor publishing education in ethics and humanistic values and reaffirmed BIGC’s commitment to building a global talent platform through AIPE.
BIGC will deepen academic-industry collaboration through AIPE to provide a premium platform for nurturing high-level, holistic, and internationally competent publishing talent, he added.
Zhang Xin, secretary of the CPC Committee at BIGC, emphasized that AIPE is expected to help globalize Chinese publishing scholarships, contribute new ideas to the industry, and cultivate a new generation of publishing professionals for the digital era.
Themed “Mutual Learning and Cooperation: New Ecology of International Publishing Education in the Digital Intelligence Era”, the conference also tackled a wide range of challenges and opportunities brought on by AI — from ethical concerns and content ownership to protecting human creativity and rethinking publishing values in higher education.
Wu Shulin, president of the Publishers Association of China, cautioned that while AI brings major opportunities, “we must not overlook the ethical and security problems it introduces”.
Catriona Stevenson, deputy CEO of the UK Publishers Association, echoed this sentiment. She highlighted how British publishers are adopting AI to amplify human creativity and productivity, while calling for global cooperation to protect intellectual property and combat AI tool infringement.
The conference aims to explore innovative pathways for the publishing industry and education reform, discuss emerging technological trends, advance higher education philosophies and talent development models, promote global academic exchange and collaboration, and empower knowledge production and dissemination through publishing education in the digital intelligence era.
yangyangs@chinadaily.com.cn
Publishing stands at a pivotal juncture, said Jeremy North, president of Global Book Business at Taylor & Francis Group, addressing delegates at the 3rd International Conference on Publishing Education in Beijing. Digital intelligence is fundamentally transforming the sector — and this revolution will inevitably create “AI winners and losers”.
True winners, he argued, will be those who embrace AI not as a replacement for human insight but as a tool that strengthens publishing”s core mission: connecting people through knowledge. The key is balance, North said, using AI to enhance creativity without diminishing human judgment or critical thinking.
This vision set the tone for the event where the Association for International Publishing Education was officially launched — the world’s first global alliance dedicated to advancing publishing education through international collaboration.
Unveiled at the conference cohosted by the Beijing Institute of Graphic Communication and the Publishers Association of China, the AIPE brings together nearly 50 member organizations with a mission to foster joint research, training, and innovation in publishing education.
Tian Zhongli, president of BIGC, stressed the need to anchor publishing education in ethics and humanistic values and reaffirmed BIGC’s commitment to building a global talent platform through AIPE.
BIGC will deepen academic-industry collaboration through AIPE to provide a premium platform for nurturing high-level, holistic, and internationally competent publishing talent, he added.
Zhang Xin, secretary of the CPC Committee at BIGC, emphasized that AIPE is expected to help globalize Chinese publishing scholarships, contribute new ideas to the industry, and cultivate a new generation of publishing professionals for the digital era.
Themed “Mutual Learning and Cooperation: New Ecology of International Publishing Education in the Digital Intelligence Era”, the conference also tackled a wide range of challenges and opportunities brought on by AI — from ethical concerns and content ownership to protecting human creativity and rethinking publishing values in higher education.
Wu Shulin, president of the Publishers Association of China, cautioned that while AI brings major opportunities, “we must not overlook the ethical and security problems it introduces”.
Catriona Stevenson, deputy CEO of the UK Publishers Association, echoed this sentiment. She highlighted how British publishers are adopting AI to amplify human creativity and productivity, while calling for global cooperation to protect intellectual property and combat AI tool infringement.
The conference aims to explore innovative pathways for the publishing industry and education reform, discuss emerging technological trends, advance higher education philosophies and talent development models, promote global academic exchange and collaboration, and empower knowledge production and dissemination through publishing education in the digital intelligence era.
yangyangs@chinadaily.com.cn
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