In January, I had the privilege of delivering the keynote at EDGO 2025. There were so many fantastic questions – too many to get to during the event. Afterwards, I got a note from the CEO of Measured Strategies, Karen Menard, with a great question: “One of the things I keep hearing about is the increasing need for data and AI ethics focused roles and I’m really curious as to how you see those roles and skills evolving over the coming years.” 

My paraphrased interpretation …

How can organizations build capacity for data and AI ethics work?

To add a little more context, Karen also shared that she works with many non-profits and organizations where there are a range of demands related to data. Hiring new roles that are solely focused on ethics would be challenging given limited resources and other data areas that need to be addressed. 

Before I get to some thoughts on this question, I want to say thanks to Karen for reaching out and for giving me permission to share this question for the column. 

Recognizing Data Ethics: Build Awareness

This question really resonates with me because before starting my company, I used to run a not-for-profit organization in Canada. We had a monthly donor program and processed thousands of transactions a month. As a media outlet, we also had a lot of data related to running the broadcast operations including an extensive digital music library. Like so many not-for-profit organizations (and small businesses), we never seemed to have enough staff to meet every need. Our ‘data work’ fell to the functional department and at that time I didn’t even think about it in terms of data work. It was simply fund development, finance, HR or programming. But, from my current vantage point – it relates to data and there were many choices being made with ethical implications.

One of the ethical data decisions we “accidentally” made during that time was related to keeping our data stored in Canada. This was a time when the “no fly list” was making headlines. I’d heard through the grapevine about a donor in our community who was concerned about safeguarding their personal data in light of the (now expired) Patriot Act. This story led me to ask our software vendor a bunch of questions about servers and where data was actually being kept. I want to stress the serendipitous nature of stumbling onto this issue. I wish I could say it was strategic – but the truth is, it was a happy accident.

I share this story because I believe leaders do care about ethics and about data, but perhaps don’t always make the connection between these areas. It wasn’t necessarily obvious to me back in my not-for-profit leadership days (which feels shocking to admit now!) but it’s a reality for people who are not immersed in data work and who are stretched to capacity with a myriad of issues. At the time, I had no background in data ethics to understand what ethical issues I should be concerned about and others in the organization were also uninformed. So, the first piece of advice is to build awareness with leadership about the connection between data and ethics. Stories are a good way to do that. 

Prioritizing Data Ethics: Whose Job Is This?

Once there is awareness, getting agreement that data ethics is important in principle isn’t all that difficult. However, getting resources to do the actual work in practice can be a challenge – especially for smaller organizations. Likely there isn’t the budget for someone whose sole job is “data ethics.” Even in very large organizations, there might be few resources whose official job is focused on this area. 

What are some practical ways to accomplish the work?

• Start with existing team members. Cross-training existing team members is a practical and actionable step. This should include at least one leadership (executive level) role in addition to a technical role (IT, cybersecurity, database administrator). If volunteers are being asked to enter data, they can also be trained to understand specific issues – for example, the importance of data quality as it relates to data ethics. 
• Augment with specialists. Similar to how you might use legal counsel or an expert in any professional area, you can seek out a data or AI ethics consultant to help answer a specific question, work on a project that is highly data ethics intensive, conduct staff training sessions to build internal capacity, or help set up a program to manage data ethics issues.

What Background, Competencies, and Skills Are Needed?

There isn’t one path into the work of data or AI ethics. Rather, the area benefits from having people who have been led to this work from a variety of areas. In some cases, people have what might be considered more of a traditional data background. That might include roles in data governance and data management or data privacy. Yet, there are also many people working in this area who have come from non-data-related and non-technical areas. Sometimes they have formal training in philosophy and ethics, or they may have a social science or arts and humanities background. 

Depending on where you enter the field points towards the skills you might need to develop to be able to understand not only the ethical issues but also how those issues play out in terms of data and/or AI technologies. If you come from a strong background with formal ethics or legal (privacy) training, you may need to upskill your technical understanding of data and how it is used in machine learning. Vice versa for someone who comes from a technical background and wants to incorporate data ethics into their work. 

Critical thinking skills are essential as well as an understanding of computational thinking and how algorithms work. This type of work also involves collaboration and working across teams, so good people skills, relational and communication skills are needed. It helps to be a team player and consensus builder. I also really like this post from the UK’s data government blog which offers more details about competencies.

Right now, the field is still fairly new. There isn’t a formal playbook to follow, though there are a range of courses, books, and other resources that can help to inform the work. In addition to skills it helps to have some of these aptitudes:

• Curiosity – someone interested in many things, learning new things
• Pioneering spirit – being OK working without a set “playbook”
• Courage – being able to speak up or take a contrarian position
• Diplomacy – tactfully “speak truth to power” in ways that help elicit positive action

I love this set of posts from b cavello about their journey into AI policy work which is a related area. It echoes some of the things I’ve mentioned but also provides additional insights and resources.

How Will This Work Evolve? Generalist to Specialist

Right now there is a lot of room for generalists. Part of this relates to the work being very new. New fields tend to attract people who like being pioneers and hacking their own path through the jungle, so to speak. That notion of generalist also fits well with a lack of maturity within organizations. It’s easier to have one person wear many hats, and the hats one tends to wear also speak to how they entered the field (e.g., from the privacy side, the technical side, etc). 

As fields start to mature, we tend to see more resources allocated to the work and more division of labor. In a more mature and often larger setting, this looks like a team of people who have deeper expertise in their respective areas – privacy, cybersecurity, data governance, and ethics – who come together to do the work. This can call for deeper but narrower expertise. For example, while consulting with a government client on data ethics, there was a team already in place that handled privacy. They had deep expertise in the privacy laws for that jurisdiction. My work was to collaborate with that team to offer another perspective focused more broadly on ethical issues. 

I also see domain expertise as becoming more important as this work matures. Right now data and AI ethics work tends to cut across industries, similar to professions such as accounting. Yet, as the field grows, there is the opportunity to carve out domain specific expertise (e.g., healthcare, education, the financial sector). 

Send Me Your Questions!

I would love to hear about your data dilemmas or AI ethics questions and quandaries. You can send me a note at hello@ethicallyalignedai.com or connect with me on LinkedIn. I will keep all inquiries confidential and remove any potentially sensitive information – so please feel free to keep things high level and anonymous as well. 

This column is not legal advice. The information provided is strictly for educational purposes. AI and data regulation is an evolving area and anyone with specific questions should seek advice from a legal professional.