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Ethics & Policy

12 top resources to build an ethical AI framework

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As generative AI (GenAI) gains a stronger foothold in the enterprise, executives are called upon to bring greater attention to AI ethics, moral principles and methods that help shape the development and use of AI technology.

An ethical approach to AI is important, not only to making the world a better place but also to protecting a company’s bottom line, since it involves understanding the financial and reputational impact of biased data, hallucinations, transparency, explainability, limitations and other factors that erode public trust in AI.

“The most impactful frameworks or approaches to addressing ethical AI issues … take all aspects of the technology — its usage, risks and potential outcomes — into consideration,” said Tad Roselund, managing director and senior partner at Boston Consulting Group.

Many firms approach the development of ethical AI frameworks from a purely values-based position, Roselund said. It’s important to take a holistic, ethical AI approach that integrates strategy with process and technical controls, cultural norms and governance. These three elements of an ethical AI framework can help institute responsible AI policies and initiatives. And it all starts by establishing a set of principles around AI usage.

“Oftentimes, businesses and leaders are narrowly focused on one of these elements when they need to focus on all of them,” Roselund reasoned. Addressing any one element might be a good starting point, but by considering all three elements — controls, cultural norms and governance — businesses can devise an all-encompassing ethical AI framework. This approach is especially important when it comes to GenAI and its ability to democratize the use of AI.

Enterprises must also instill AI ethics in those who develop and use AI tools and technologies. Open communication, educational resources, and enforced guidelines and processes to ensure the proper use of AI, Roselund advised, can further bolster an internal AI ethics framework that addresses GenAI.

Several issues need to be considered and overcome when devising and establishing an AI ethics framework.

Top resources to shape an ethical AI framework

The following is an alphabetical list of standards, tools, techniques and other resources to help shape a company’s internal ethical AI framework.

1. AI Now Institute

The institute focuses on the social implications of AI and policy research in responsible AI. Research areas include algorithmic accountability, antitrust concerns, biometrics, worker data rights, large-scale AI models and privacy. The April report “AI Now 2023 Landscape: Confronting Tech Power” provides a deep dive into many ethical issues that can be helpful in developing a responsible AI policy.

2. Berkman Klein Center for Internet & Society at Harvard University

The center fosters research into the big questions related to the ethics and governance of AI. It has contributed to the dialogue about information quality, influenced policymaking on algorithms in criminal justice, supported the development of AI governance frameworks, studied algorithmic accountability and collaborated with AI vendors.

3. CEN-CENELEC Joint Technical Committee 21 on Artificial Intelligence

JTC 21 is an ongoing EU initiative for various responsible AI standards. The group focuses on producing standards for the European market and informing EU legislation, policies and values. It also plans to specify technical requirements for characterizing transparency, robustness and accuracy in AI systems.

4. Institute for Technology, Ethics and Culture Handbook

The ITEC Handbook was a collaborative effort between Santa Clara University’s Markkula Center for Applied Ethics and the Vatican to develop a practical, incremental roadmap for technology ethics. The handbook includes a five-stage maturity model with specific, measurable steps that enterprises can take at each level of maturity. It also promotes an operational approach for implementing ethics as an ongoing practice, akin to DevSecOps for ethics. The core idea is to bring legal, technical and business teams together during ethical AI’s early stages to root out bugs at a time when they’re much cheaper to fix than after responsible AI deployment.

5. IEEE Global Initiative 2.0 on Ethics of Autonomous and Intelligent Systems

The initiative focuses on ethical issues with incorporating GenAI into future autonomous and agentic systems. In particular, the group is exploring how to extend traditional safety concepts to include scientific integrity and public safety as priorities. Of note, they are exploring how the concept of safety has sometimes been misappropriated and misunderstood with regard to new GenAI risks. This working group is developing new standards, toolkits, AI safety champions and awareness campaigns to improve the ethical use of GenAI tools and infrastructure.

6. ISO/IEC 23894:2023

The standard describes how an organization can manage risks specifically related to AI. It can help standardize the technical language characterizing the underlying principles and how these principles apply to developing, provisioning or offering AI systems. It also covers policies, procedures and practices to assess, treat, monitor, review and record risk. It’s highly technical and oriented toward engineers rather than business experts.

7. NIST AI Risk Management Framework

AI RMF 1.0 guides government agencies and the private sector in managing new AI risks and in promoting responsible AI. According to NIST, the framework is “intended to be voluntary, rights-preserving, non-sector-specific, and use-case agnostic.”

8. Nvidia NeMo Guardrails

The open source toolkit provides a flexible interface for defining the specific behavioral rails that bots need to follow. It supports the Colang modeling language. One chief data scientist said his company uses Nvidia NeMo Guardrails to prevent a support chatbot on a lawyer’s website from providing answers that might be construed as legal advice.

9. Partnership on AI to Benefit People and Society

PAI has been exploring many fundamental assumptions about how to build AI systems that benefit all stakeholders. Founding members include executives from Amazon, Facebook, Google, Google DeepMind, Microsoft and IBM. Supporting members include more than a hundred partners from academia, civil society, industry and various nonprofits. One novel aspect of this group has been the creation of an AI Incident Database to assess, manage and communicate newly discovered AI risks and harms. It has also explored many of the concerns related to the opportunities and harms of AI-generated content.

10. Stanford Institute for Human-Centered Artificial Intelligence

HAI provides ongoing research and guidance into best practices for human-centered AI. One early initiative in collaboration with Stanford Medicine is Responsible AI for Safe and Equitable Health, which addresses ethical and safety issues surrounding AI in health and medicine.

11. “Towards Unified Objectives for Self-Reflective AI” paper

This paper by Matthias Samwald, Robert Praas and Konstantin Hebenstreit takes a Socratic approach to identify underlying assumptions, contradictions and errors through dialogue and questioning about truthfulness, transparency, robustness and alignment of ethical principles. One goal is to develop AI meta-systems in which two or more component AI models complement, critique and improve their mutual performance.

12. World Economic Forum’s “The Presidio Recommendations on Responsible Generative AI” white paper

This June 2023 white paper includes 30 “action-oriented” recommendations to “navigate AI complexities and harness its potential ethically.” It includes sections on responsible development and release of GenAI, open innovation and international collaboration, and social progress.

Assessing a company's AI landscape
Establishing an ethical AI framework and instituting responsible AI practices require a comprehensive assessment of AI processes companywide.

Best ethical AI practices

Ethical AI resources are a sound starting point toward tailoring and establishing a company’s ethical AI framework and launching responsible AI policies and initiatives. The following best practices can help achieve these goals:

  • Appoint an ethics leader. There are instances when many well-intentioned people sit around a table discussing various ethical AI issues but fail to make informed, decisive calls to action, Roselund noted. A single leader appointed by the CEO can drive decisions and actions.
  • Take a cross-functional approach. Implementing AI tools and technologies companywide requires cross-functional cooperation, so the policies and procedures to ensure the responsible use of AI need to reflect that approach, Roselund advised. Ethical AI requires leadership, but its success isn’t the sole responsibility of one person or department.
  • Customize the ethical AI framework. A GenAI ethics framework should be tailored to a company’s unique style, objectives and risks. Harmonize ethical AI programs with existing workflows and governance structures.
  • Establish ethical AI measurements. For employees to buy into an ethical AI framework and responsible AI policies, companies need to be transparent about their intentions, expectations and corporate values, as well as their plans to measure success. “Employees not only need to be made aware of these new ethical emphases, but they also need to be measured in their adjustment and rewarded for adjusting to new expectations,” explained Brian Green, director of technology ethics at Santa Clara University’s Markkula Center for Applied Ethics.
  • Be open to different opinions. It’s essential to engage a diverse group of voices, including ethicists, field experts and those in surrounding communities that AI deployments might affect. “By working together, we gain a deeper understanding of ethical concerns and viewpoints and develop AI systems that are inclusive and respectful of diverse values,” said Paul Pallath, vice president of the applied AI practice at technology consultancy Searce.
  • Take a holistic perspective. Legalities don’t always align with ethics, Pallath cautioned. Sometimes, legally acceptable actions might raise ethical concerns. Ethical decision-making needs to address both legal and moral aspects. This approach ensures AI technologies meet legal requirements and uphold ethical principles to safeguard the well-being of individuals and society.

Future of ethical AI frameworks

Researchers, enterprise leaders and regulators are still investigating ethical issues related to responsible AI. Increasingly, enterprises will need to consider ethics, not just as a liability and checkmark item but as a lens to expand opportunities for collecting better data and building trust with customers and regulators.

Legal challenges involving copyright and intellectual property protection will also have to be addressed. Issues related to GenAI and hallucinations will take longer to address, since some of those potential problems are inherent in the design of today’s AI systems. In the U.S., copyright regulators have agreed that AI-generated content is copyrightable with some level of human involvement. There are still many question marks relating to training data, which sometimes includes copyrighted content, violation of terms of service and even blatant pirating of copyrighted works by large AI developers like Meta. The courts are still deciding these matters, and risk-averse companies might consider steering clear of the AI tools and services built on some of these practices — even when they are proffered as “open AI.”

Enterprises and data scientists will also need to solve issues of bias and inequality in training data and machine learning algorithms. In addition, issues relating to AI system security, including cyberattacks against large language models, will require continuous engineering and design improvements to keep pace with increasingly sophisticated criminal adversaries. The NIST AI Risk Management Framework could help mitigate some of these concerns.

In the near future, Pallath sees AI evolving toward enhancing human capabilities in collaboration with AI technologies rather than supplanting humans entirely. “Ethical considerations,” he explained, “will revolve around optimizing AI’s role in augmenting human creativity, productivity and decision-making, all while preserving human control and oversight.”

AI ethics will continue to be a fast-growing movement for the foreseeable future, Green said. “With AI,” he acknowledged, “now we have created thinkers outside of ourselves and discovered that, unless we give them some ethical thoughts, they won’t make good choices.”

AI ethics is never done. Ethical judgments might need to change as conditions change. “We need to maintain our awareness and skill,” Green said, “so that, if AI is not benefiting society, we can make the necessary improvements.”

For example, new GenAI tools could give nations a leg up in critical areas such as warfare or more effective cyberattacks, yet merely developing these tools could also empower adversaries. This could result in a zero-sum situation that benefits no one and costs money in the process. These issues are getting thornier, particularly with the growth of open source AI that could also empower nation-states and malicious adversaries. However, stifling open source AI development could also disempower more efficient and effective AI development in the long run.

Editor’s note: This article was updated in March 2025 to include additional ethical AI framework resources.

George Lawton is a journalist based in London. Over the last 30 years, he has written more than 3,000 stories about computers, communications, knowledge management, business, health and other areas that interest him.



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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

Preparing Timor Leste to embrace Artificial Intelligence

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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.



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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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