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Ethics & Policy

AI ethics: what are the limits in healthcare?

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AI has worked its way into many industries over the past decade with no end in sight. The world of healthcare has been no exception, but it has been one of the spaces in which public reception to AI’s implementation has been the most hesitant.

Research by the US Pew Research Centre found the public generally split on the issue, with 60% of those surveyed as part of a nationwide study stating they would be somewhat or very uncomfortable if their healthcare provider were to rely on technology for jobs such as diagnoses and treatment recommendations.

The survey also found that only 38% of Americans believe the use of AI in healthcare would lead to better outcomes whilst only 33% thought it would make it worse, the rest were ambivalent or didn’t know.

Despite concerns, the global healthcare industry has pushed ahead when it comes to implementing the technology, from patient medical records in hospital management to drug discovery and surgical robotics. In the field of medical devices alone research by GlobalData estimates that the market is set to be worth $477.6bn by 2030.

If AI will become ubiquitous and involved in some of the most important decisions in a person’s life, what is the appropriate moral or ethical set of rules for it to which it adheres? What are the ethical upper limits of AI and where does it become unethical to implement the technology?

To find out more, Medical Device Network sat down with David Leslie, director of ethics and responsible innovation research at The UK’s Alan Turing Institute, to understand what set of rules AI should be applied in healthcare.

This interview has been edited for length and clarity.

Joshua Silverwood (JS): Tell me about how you started to research this subject.

David Leslie (DL): So, I started to really think more deeply about this during the Covid-19 pandemic because the Turing Institute was working on a project that was supposed to be a rapid response, data scientific approach to asking and answering all kinds of medical questions or biomedical questions about the disease.

I got AI to write an article in the Harvard Data Science Review at the time called “Tackling Covid-19 through responsible AI innovation” and it went through some of the deeper issues around biases and the big picture issues and how these were manifesting in the pandemic. It was called – does AI stand for augmenting inequality in the Covid-19 era of healthcare?

Off the back of that, I was asked by the Department of Health and Social Care (DHSC) to support a rapid review into HealthEquity in AI-enabled medical devices.

JS: What practical examples of AI worsening inequality have you noticed in your research?

DL: I think we can even do it the other way, which is looking at how patterns of inequality and inequity in the world come to find their way into the technology. So first and foremost, we can talk about how social determinants of health play a role. Places where we live create different inequities. So, things like inequities in access to health care inequities in admission and treatment, and unequal resource allocation based upon the particular environments.

There are also biases that manifest in medical training where they privilege certain socio-economic groups in the way that they train. If you are being trained as a dermatologist, it is more likely that you will have deep knowledge of lighter skin tones but not so much knowledge of darker skin tones. So, all these components, they come to be elements that seep into the AI lifecycle.

For instance, inequitable access to medical services will lead to representational imbalances in data sets. You will have data distributions that may not include certain minority groups in the right way because they haven’t been taken up in electronic health records by virtue of gaps in the service.

JS: Can certain social misconceptions be borne out in AI?

DL: So just think of the pathway AI takes. Let’s say I am a doctor and you come into my clinic for an assessment. In our interaction, my biases will manifest in my notes. So, when you aggregate that and see that X many doctors have X many notes and all those notes will be used to fine-tune a natural language processing system, one that may be used to support something like triaging or suggestions for some type of path treatment pathways.

It would be illogical to think that when you move from biased clinical notes to the outputs of a natural language processing system, somehow magically the biases would disappear because they’re baked into the data sets.

So, we must be very careful, I think. These are social practices first and foremost and the baked-in biases will manifest across the data.

JS: Is there any set of codifiable rules for AI to work by that would mitigate these biases?

DL: Inequity and bias, in a sense, we shouldn’t talk about eliminating it because these are kind of operative in our world, and we always need to think about how we mitigate them in technology. How do we lessen the impact and improve the systems based on our attempts to mitigate discrimination and bias? We must be aware that bias will crop up just by humans being humans.

For me, the most important methodologies are those that are anticipatory, so that they incorporate reflective bias mitigation processes into the design of the systems.

JS: Are there any areas of healthcare you feel are too sensitive to allow for AI?

DL: I think we need to just be very aware that zero questions matter. When I say that, I mean that there are such a diverse range of AI-supported technologies that are available, but also there are certain problems that are of a complex and social nature that may not be as amenable to being supported by statistical systems. These are all computational statistical systems. There is a call for a little bit more practical judgment and common sense.

Do I think that there are other challenging cases? For instance, in insurance, we have glaring examples of how millions of people have been discriminated against. There is no one sickness score. The reason why we must be more contextually responsive to complex social problems is that when you’re processing social and demographic data, you are going to see more social biases and reverberations of patterns of harm in that data.






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Ethics & Policy

AI and ethics – what is originality? Maybe we’re just not that special when it comes to creativity?

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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



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Ethics & Policy

Experts gather to discuss ethics, AI and the future of publishing

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Representatives of the founding members sign the memorandum of cooperation at the launch of the Association for International Publishing Education during the 3rd International Conference on Publishing Education in Beijing.CHINA DAILY

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.

 

 

 



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Ethics & Policy

Experts gather to discuss ethics, AI and the future of publishing

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Representatives of the founding members sign the memorandum of cooperation at the launch of the Association for International Publishing Education during the 3rd International Conference on Publishing Education in Beijing.CHINA DAILY

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.

 

 

 



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