Ethics & Policy
AI Boost or Bust? – Syracuse University
Amid the philosophical and ethical issues swirling around the booming artificial intelligence (AI) revolution—from questions about privacy, safety risks and surveillance to generative AI deepfakes, AI companionship and AI systems going rogue—Syracuse University professor Johannes Himmelreich views its use with guarded optimism. “I think there is a good way of using AI and I want to contribute to finding it,” he says. “We should be using AI, but the question is how should we use it?”
Himmelreich has long been fascinated by the role of philosophy and ethics in technology. And as the landscape of AI rapidly expands, he is investigating its impact on society. “I have interests across a whole range of topics in philosophy, and what binds many of them together is their association with AI,” says the associate professor of public administration and international affairs in the Maxwell School of Citizenship and Public Affairs. “I’m drawn to issues that intersect with emerging social topics or use new methods. That’s why computation and AI are an attractive topic for me to work on—so many changes coming into philosophy today are from these areas.”
Himmelreich is focused on AI’s use in government and its role in decision-making, as well as AI regulations and policy. He’s co-editor of The Oxford Handbook of AI Governance (Oxford University Press, 2024), which examines the challenges and opportunities at the intersection of AI and governance. His interest in politics, social justice, computation and the digital economy often spark his interdisciplinary approach to research. He’s delved into such topics as killer robots and self-driving cars. With the support of a two-year grant from the National Endowment for the Humanities, Himmelreich is working on a book about the philosophy and ethics of data science and good decision-making. “If data science is about supporting decision-making, then you want to make sure the decisions are fair and don’t harm people,” he says.
Deliberating Data’s Ethical Dilemmas
Data-driven decision-making is deeply embedded in today’s world, offering informed choices through analysis designed to improve performance. The process is routinely accepted as factual and accurate—a fail-safe counter to “gut instinct” decisions. But for all the successes, if data is flawed, it can lead to unforeseen problems. And since massive datasets fuel AI, Himmelreich sees inherent ethical dilemmas associated with data—bias and privacy risks, for instance. His current focus is on how data science methods that researchers use to collect, clean, analyze, model and present data can unintentionally distort the truth.
“The question—What is good data?—is not as easy to answer as you might think, because good data is sometimes made up, generated by what’s called synthetic data,” he says.
Synthetic data is artificially generated information that resembles real data, mimicking its patterns, relationships, and structures. Although the information isn’t collected from actual people or events, it is used to test and train AI models.
Often this type of data drives AI’s progress—in applications such as ChatGPT, facial recognition and tabular data. “AI becomes smarter with more data, and the more data you have, the better your AI is,” Himmelreich says. “That scaling law holds also from made-up data. The algorithm doesn’t care if the data is real or not. It just wants more.”
If the original data is distorted, the synthetic data can inherit that distortion. “The sinister part is not that synthetic data is made up,” he says. “You might not even know it’s happening because to show distortion you need to have data, and oftentimes you don’t have the data to show there’s a distortion.”
Maxwell School professor Johannes Himmelreich is interested in examining how data science methods used by researchers can unintentionally distort the truth.
Employing AI in Government Decision-Making
Himmelreich highlights one routine example of AI employed in the public sector: The Social Security Administration uses AI to help decide who qualifies for disability benefits—bringing automation into some of the most critical, human-centered decisions in government. AI systems are trained to detect fraud, seemingly making it simpler to process claims and decisions, but they produce both false positives and negatives.
This raises the ethical issue of which mistake is worse: denying an individual’s legitimate claim, which could jeopardize their livelihood, or missing a fraudulent case that will cost taxpayers. “The challenge is to figure out which mistakes are you more willing to accept given that you will make mistakes,” he says.
An appropriate use of AI, Himmelreich believes, is in sorting cases based on their difficulty, prompting decision-makers to grant more attention to challenging cases. “That’s not just true for disability insurance or unemployment insurance, it’s also true in the medical sector,” he says. “We are already using AI for cancer diagnosis and assisting radiologists in reading medical imaging.”
Himmelreich believes that problems in AI projects often happen at the point where humans and machines interact. To prevent these breakdowns, he says it’s important to have a clear goal, a well-defined step-by-step process and strong communication. “Good data science is exactly at this interface and not necessarily in the technical analysis,” he says. “The really important skill for data scientists is to understand the situation of the decision-makers they’re supporting and produce something that augments their work and helps them make better decisions.”
In his Philosophy and Ethics of Data Science graduate course, Himmelreich emphasizes that data science involves countless dilemmas, trade-offs and value conflicts. “I want my students to have the knowledge and methods to solve those dilemmas and to have confidence in their ability to solve them,” he says.
Balancing Benefits and Harms
From the early beginnings, safety concerns have gone hand in hand with AI. Himmelreich cautions that the more prevalent AI’s use becomes in government and other areas, the more risk is introduced. “The harms that can come from AI can be much more nefarious because they’re harder to detect,” he says. “The question of how we control AI is really relevant.”
Himmelreich is drawn to how technologies are designed and built and understanding how they’re implemented—for better or worse. Ultimately, he hopes AI enhances society, providing support where it’s needed, rather than replacing us. This will enable us to excel in our strengths and reap the rewards of AI while acknowledging its limitations and guarding against erroneous behavior. “To me,” he says, “the ethical questions are super important because over the next few years we will make important decisions about how we’re going to use AI.”
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
Ethics & Policy
Experts gather to discuss ethics, AI and the future of publishing
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
Ethics & Policy
Experts gather to discuss ethics, AI and the future of publishing
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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