Ethics & Policy
Governance, legal transformation and the ethics of emerging tech
Kay Firth-Butterfield, the previous inaugural Head of AI and Machine Learning at the World Economic Forum, explores how to build trustworthy AI and the changing pros and cons of generative AI
Ranked among the world’s foremost artificial intelligence speakers, Kay Firth-Butterfield is a trailblazer in AI ethics and governance. She was the world’s first Chief AI Ethics Officer and served as the inaugural Head of AI and Machine Learning at the World Economic Forum.
Named to the TIME100 Impact List and Forbes 50 Over 50: Innovation, her influence spans policy, law, business, and education. In this exclusive interview with Champions Speakers Agency, she shares her insights on responsible AI adoption, the promise and pitfalls of generative AI, and how technology is set to transform the legal profession and beyond.
Q: As AI capabilities rapidly expand, what key principles should guide businesses in deploying artificial intelligence responsibly and effectively?
That’s a huge question, because there are so many ways AI can be used in a business. But I’d say to use it successfully, you need to be very aware of the responsible—or trustworthy—aspects of artificial intelligence.
You shouldn’t deploy AI—or, if you’re creating it yourself, design and develop it—without keeping ethics in mind. We call it ‘responsible’ or ‘trustworthy AI’ now, because those factors might affect successful deployment if you don’t get it right.
There’s the possibility of serious damage to a company, not just brand or customer loss, but financial loss too. More and more regulators are starting to sue those using AI irresponsibly, or without built-in trust. No one wants to be seen as untrustworthy with AI—it’s not a good look.
Where to deploy AI? Some common uses are in human resources, such as helping with talent spotting. However, there are big problems with using AI in HR because it can bring in human biases. We’re seeing some lawsuits in the US where companies unwisely bought AI for HR and are being sued for using discriminatory tech. You have to be really careful—it’s a balance between AI’s benefits and thoroughly thinking through buying and deploying these systems.
Other AI business uses? Manufacturing companies across factory floors, and drug companies to help design pharmaceuticals. For example, DeepMind’s AlphaFold enabled big advances in using AI for biological work.
There’s generative AI, which everyone’s talking about. You could use it in business, but be really aware that if you use models like ChatGPT, the data you feed it goes in and could come out anywhere. Don’t give it trade secrets. We saw a confidential Samsung memo get leaked globally when an employee had ChatGPT transcribe it.
So, if you’re using generative AI in business, understand what AI is. It just predicts the next word—it’s not actually intelligent. Let teams play with it after your legal department greenlights it, and your C-suite understands AI and how you use it, with guidelines from your CTO or CIO.
Q: In the context of accelerating digital transformation, why is it essential for organisations to engage with emerging technologies, and how can they do so without falling into common implementation pitfalls?
I think it’s important to make use of the latest technologies in the same way as it would have been important for Kodak to notice there was a change coming in the photography industry. Businesses that don’t at least look at digital transformation are going to find themselves on the back foot.
But a word of caution here: you can also go hell for leather and then find that you have the wrong AI or the wrong systems for your business. I would say that it’s really important to practise caution, keep your eyes open, and think about this as a business decision every step of the way.
It’s particularly important when you decide that yes, you’re ready to use artificial intelligence to, I would say, hold your suppliers’ feet to the fire—ask the right questions, ask detailed questions. Make sure you have somebody in-house or a consultant who will enable you to ask the right questions. Because, as we all know, one of the greatest wastes of money in digital transformation is if you don’t ask the right questions and do it correctly.
Q: Generative AI is transforming how we interact with content and data. In your view, what are the most significant benefits it offers, and what risks should we be paying attention to?
All of us can use AI now—it’s a hugely democratising tool. It means small and medium-sized enterprises that could not have used AI in the past can now do so.
When we talk about it, we also need to recognise that all the data—and the bulk of the data in the world—is created in America first, and then Europe and China.
There are several data challenges in terms of the data that these large language models are using. They’re not actually using the world’s data—they’re using a small subset—and we are beginning to talk about digital colonisation. We’re projecting content derived from data from America and Europe to the rest of the world, and also expecting them to use that content.
Obviously, different cultures need different answers. So, there are lots and lots of really beneficial parts of generative AI, but also some really big challenges ahead of us.
Q: From your perspective, how will technologies like generative AI reshape the legal profession—and what implications could this have for training, ethics, and access to justice
When we talk about the legal system, I think we’re not only talking about the legal system, but other professions as well—like medicine, accountancy, insurance, early and middle management in business.
With generative AI, it can do tasks we currently give to young lawyers, like taking notes and transcribing recordings—so you won’t need them for that anymore.
It can research, if it has access to the right databases—but there’s a lot of discussion about it potentially breaching copyrights and IP. If it only has open internet data, it won’t access proprietary sources behind paywalls. You have to be careful when deploying it that it has the data you actually need. But if so, it can research quicker than humans.
It can write emails; we may see paralegals and junior lawyers disappear across professions and businesses.
Is that a good thing? It cuts legal costs, helping access, but challenges training and experience building. How do you become a senior partner without that junior role?
Clients will cite machine advice and question human lawyers. We must interact carefully—like pilots using autopilot. Blind faith in AI causes issues, as we’ve seen with sentencing tools—judges just following them, versus combining strengths.
There are major changes coming—for law and beyond.
This exclusive interview with Kay Firth-Butterfield was conducted by Mark Matthews.
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
Preparing Timor Leste to embrace Artificial Intelligence
UNESCO, in collaboration with the Ministry of Transport and Communications, Catalpa International and national lead consultant, jointly conducted consultative and validation workshops as part of the AI Readiness assessment implementation in Timor-Leste. Held on 8–9 April and 27 May respectively, the workshops convened representatives from government ministries, academia, international organisations and development partners, the Timor-Leste National Commission for UNESCO, civil society, and the private sector for a multi-stakeholder consultation to unpack the current stage of AI adoption and development in the country, guided by UNESCO’s AI Readiness Assessment Methodology (RAM).
In response to growing concerns about the rapid rise of AI, the UNESCO Recommendation on the Ethics of Artificial Intelligence was adopted by 194 Member States in 2021, including Timor-Leste, to ensure ethical governance of AI. To support Member States in implementing this Recommendation, the RAM was developed by UNESCO’s AI experts without borders. It includes a range of quantitative and qualitative questions designed to gather information across different dimensions of a country’s AI ecosystem, including legal and regulatory, social and cultural, economic, scientific and educational, technological and infrastructural aspects.
By compiling comprehensive insights into these areas, the final RAM report helps identify institutional and regulatory gaps, which can assist the government with the necessary AI governance and enable UNESCO to provide tailored support that promotes an ethical AI ecosystem aligned with the Recommendation.
The first day of the workshop was opened by Timor-Leste’s Minister of Transport and Communication, H.E. Miguel Marques Gonçalves Manetelu. In his opening remarks, Minister Manetelu highlighted the pivotal role of AI in shaping the future. He emphasised that the current global trajectory is not only driving the digitalisation of work but also enabling more effective and productive outcomes.
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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