Ethics & Policy
AI Governance That Powers Ethical Innovation
The Gist
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Ethical foundations matter. Strong AI governance builds trust, prevents bias and facilitates compliance.
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Proactive risk management. Addressing bias, traceability and transparency early minimizes reputational, legal and operational risks while strengthening AI’s reliability.
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Continuous adaptation needed. AI governance is an ongoing effort, and it requires dynamic frameworks, stakeholder feedback and regular audits.
The rise of artificial intelligence has reshaped industries, processes and how we interact with technology. However, with great power comes great responsibility. Embedding ethics and governance in AI isn’t just a “nice-to-have.” It’s a necessity.
As organizations rush to adopt AI, making sure these systems are ethical, transparent and well-governed is critical to build customer trust and avoid unintended consequences. Here’s how you can make ethics and AI governance central to your AI efforts.
Table of Contents
Understanding the Risks of Poor AI Governance
Incorporating robust ethical standards and governance in AI solutions is not merely a moral imperative but a business necessity. Neglecting these aspects can lead to significant risks, including loss of trust, flawed analytics and legal repercussions.
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Loss of Trust: Trust is foundational for any business. AI systems perceived as unethical or biased can erode customer confidence, which leads to reputational damage. For example, Amazon’s AI recruitment tool was found to favor male candidates due to biased training data. This led to the tool’s discontinuation and tarnished Amazon’s reputation.
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Flawed Analytics: AI systems lacking ethical oversight may produce biased or inaccurate outputs, which results in flawed analytics that can misguide business decisions. For example, the COMPAS algorithm, used in the U.S. criminal justice system to assess recidivism risk, was criticized for racial bias, inaccurately flagging Black defendants as high-risk more often than white defendants.
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Legal Risks: Unethical AI practices can lead to legal challenges, including lawsuits and regulatory penalties. Character.AI faced lawsuits alleging its chatbot encouraged harmful behavior among users.
Related Article: AI Trust Issues: What You Need to Know
Building a Strong Ethical AI Framework
Before diving into complex AI projects, pause and define your guiding principles. Ethics and governance need to be baked into your strategy, not just bolted on after the fact.
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Define Ethical Standards: What values does your organization stand for? Make sure these principles are reflected in your AI objectives.
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Establish Governance Early: Create an AI governance framework that includes roles, responsibilities and accountability measures for the entire AI lifecycle.
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Ensure Transparency: Avoid creating a “black box” solution with output that cannot be understood. Endeavor to build explainability and auditability into your processes.
Actionable Tip: Use version control systems and maintain clear documentation of all AI development steps.
Tackle Bias Early
Bias in AI isn’t just a technical problem; it’s an ethical one. Left unchecked, it can lead to erroneous and discriminatory outcomes that harm individuals and damage reputations.
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Diverse Data: Make sure your training datasets represent a wide range of demographics and scenarios.
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Continuous Auditing: Regularly test your models for bias and refine them based on findings.
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Cross-Functional Teams: Bring diverse voices into the AI development process, including ethicists, legal experts and underrepresented groups.
Actionable Tip: Implement fairness-aware machine learning techniques to mitigate biases during model development.
Build Traceability Into Your Systems
Traceability allows you to track the entire lifecycle of an AI system, from data sourcing to decision-making.
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Data Provenance: Keep a detailed record of where your data comes from, how it’s processed and where it’s used.
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Lifecycle Monitoring: Use tools to monitor AI performance over time and make sure it continues to align with ethical and governance standards.
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Incident Reporting: Create a mechanism for reporting and addressing unintended consequences or ethical breaches.
Actionable Tip: Adopt tools like Model Cards or Data Sheets for datasets to document the details of your AI systems transparently.
AI Governance: A Continuous Commitment
AI governance isn’t a “set it and forget it” initiative. It’s an ongoing commitment.
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Dynamic Regulation: As AI evolves, so should your AI governance frameworks. Regularly review and update them to address new challenges.
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Stakeholder Engagement: Create an environment where feedback from users and stakeholders informs governance decisions.
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Continuous Education: Equip your teams with the knowledge and tools they need to navigate the ethical and regulatory landscape.
Actionable Tip: Schedule periodic governance reviews to ensure your frameworks stay relevant and effective.
Related Article: 6 Considerations for an AI Governance Strategy
Equipping Teams for Ethical AI Development
Ethical AI begins with the people building it. Equip your teams with the right mindset, skills and resources to succeed.
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Ethical Training: Incorporate ethics into AI training programs for developers, data scientists and business leaders.
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Low-Code Tools: Empower non-technical stakeholders to participate in AI projects using accessible tools that prioritize ethical considerations.
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Culture of Accountability: Build a culture where ethical concerns are raised and addressed without fear of retaliation.
Actionable Tip: Use role-playing exercises to simulate ethical dilemmas your teams might encounter and develop their decision-making skills.
The Payoff: Trust and Sustainability
When organizations prioritize ethics and governance in their AI efforts, they don’t just avoid pitfalls. They also build systems that are trusted, scalable and resilient. By following these steps, you’ll not only comply with regulations but also create solutions that genuinely serve your customers and society.
The world of AI moves fast. Keeping ethics and governance at the heart of your AI strategy allows you to move not just quickly but also responsibly.
If you’re ready to get started, you can take one actionable step today. Review the frameworks and resources provided below to select the best approach for your needs. Use it to assess your current AI projects against these principles and identify gaps. Embedding ethics and AI governance isn’t just the right thing to do; it’s the smart thing to do.
Resources for Responsible AI Implementations
Frameworks and Templates for Embedding Governance and Ethics in AI Solutions
1. OECD AI Principles: The OECD’s AI Principles provide high-level guidance for governments and organizations on responsible AI development and use.
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Inclusive growth, sustainable development and well-being.
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Human-centered values and fairness.
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Transparency and explainability.
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Robustness, security and safety.
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Accountability.
2. AI Fairness 360 Toolkit (IBM): A comprehensive open-source toolkit developed by IBM to help developers detect and mitigate bias in machine learning models.
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Pre-built bias metrics and fairness algorithms.
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Tutorials and examples for diverse use cases.
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Tools for auditing datasets and models for fairness.
3. EU Ethics Guidelines for Trustworthy AI: The EU’s High-Level Expert Group on AI released these guidelines to make sure AI systems are lawful, ethical and robust.
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Ethical principles include respect for autonomy, prevention of harm, fairness and explicability.
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Seven requirements, including accountability, data governance, diversity and non-discrimination.
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A practical self-assessment checklist for AI projects.
4. Model Cards for Model Reporting (Google): A template for documenting machine learning models’ intended use, limitations and performance across different contexts.
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Information on datasets used for training and testing.
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Details on model performance, fairness and biases.
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Transparency in intended use and limitations.
5. AI for Good Impact Initiative: Led by the International Telecommunication Union (ITU) under the UN system, the focus of this initiative is harnessing AI to achieve the United Nations Sustainable Development Goals (SDGs). It serves as a global platform for collaboration between businesses, governments and academia to apply AI responsibly.
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Global Collaboration: Connects AI innovators with problem-owners from various industries to tackle societal challenges like climate change, healthcare and education.
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Ethical AI Deployment: Promotes the development of ethical AI solutions that align with human rights and international standards.
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Sustainability Focus: Makes sure that AI applications are designed to address pressing global issues, from poverty alleviation to environmental conservation.
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Capacity Building: Offers guidance, toolkits and resources to help organizations implement AI solutions responsibly.
6. Smart Industry Readiness Index (SIRI): Developed by the Singapore Economic Development Board, SIRI provides a structured framework to assess and improve digital and AI governance in manufacturing.
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Focuses on three pillars (process, technology and organization).
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Includes 16 dimensions for evaluating AI maturity and readiness.
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Offers a formal assessment process and improvement roadmap.
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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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