As mentioned in our previous blog post, Learn about Responsible AI with MVP Veronika Kolesnikova, it’s crucial to understand the principles of Responsible AI to ensure ethical use of AI in the future.

In this blog post, we focus on promoting an understanding of responsible AI across a broad range of audiences, from business users to high school students. We interviewed Komes Chandavimol from Thailand, who was awarded the Microsoft MVP for AI Platform in March of this year, to share his expert insights.

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Please tell us details about your recent community activities focusing on responsible AI.

In Thailand, the movement in responsible AI started with large enterprises that are exposed to the development of machine learning and attempt to apply basic responsible AI concepts such as explainable AI and reliable AI. Since then, it has become popular in two ways. First, at the community level, experts share their knowledge through sessions including meetups, podcasts, or blogs. Additionally, responsible AI is embedded into education since machine learning subjects include libraries such as SHAP or ML in operation.

As a data and AI practitioner and visiting professor, I try to encourage everyone in both ways. My Data Science Thailand page usually shares content about responsible AI concepts, toolkits, and use cases. Moreover, I have also conducted responsible AI workshops at several events from Microsoft and partner collaborations. Such events included Code; Without Barriers and SoundByte Digital Inclusion in Australia, which empower diversity efforts in our industryOn the other hand, I included responsible AI in my data science for business subject, where I teach responsible AI and focus on how to apply toolkits to ensure each principle has an example that undergraduates understand and can apply to their use cases.

Recently, I have expanded responsible AI to a wider range of audiences such as high school students. I went to a volunteering event and taught the concept of responsible AI. This includes the “Responsible AI for Young” initiative that I teach in schools to make sure students are aware of the risks in AI and how to avoid them.

What do you suggest AI users be aware of when using generative AI in terms of responsible AI?

It depends on the audience. When I conduct a class for high school students, I focus on fun and engagement, where I flip the classroom to let everyone experiment first, and then follow up with the concepts. On the other hand, if I teach younger students, I may start with a text-to-music theme and bring them to the generative AI model’s capabilities and the risks of using it in public.

In one session, I conducted responsible AI training for parents who are preparing their kids for university. This group is tech-savvy and knowledgeable about AI. The point I tried to emphasize is that they should be the “human in the loop” with their kids. Parental involvement is key to their children’s responsible AI use, and their responsibility is very important.

All in all, I believe in the concept of the 4Ps in learning: Passion, Play, Peer, and Project. I bring them to the passion with peer review and mostly give them small projects to involve and ask them to reflect on their learning with AI.

As a community leader, how do you help community members who would like to learn more about Responsible AI?

I normally give them guidelines to follow and encourage them to learn based on their interests. Many of my materials are published on my Facebook page, and I also have a small YouTube channel where I post some of the videos I teach to my students. However, I believe that today we have rich information about responsible AI, and they can connect by themselves, so I just give them shortcuts to knowledge and encourage them to learn on their own.

In conclusion, my dedication to promoting responsible AI is driven by a passion for ensuring ethical and reliable AI practices. Whether through community activities, educational initiatives, or professional workshops, I aim to inspire and equip others to navigate the complexities of AI responsibly. Through this process, I have also learned a great deal about the diverse perspectives and innovative approaches within our community, which continuously enrich my understanding and practice of responsible AI.

I look forward to continuing this journey with you all, fostering a collaborative environment where we can learn, grow, and make a positive impact together.

Thank you for your attention and commitment to responsible AI.

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Now that AI benefits are accessible to everyone, not just a select few, Komes’s efforts to raise awareness about responsible AI among various age groups are incredibly valuable. We encourage everyone reading this to explore the resources provided below to learn more about responsible AI and share this knowledge within your own communities.

– Empowering responsible AI practices | Microsoft AI

– Responsible AI Principles and Approach | Microsoft AI

– Responsible AI Solutions | Microsoft Azure

– Skill up on Responsible AI Developer Hub | Responsible AI Developer Hub (azure.github.io)

– Train a model and debug it with Responsible AI dashboard – Training | Microsoft Learn

– Embrace responsible AI principles and practices – Training | Microsoft Learn

– Responsible AI – Cloud Adoption Framework | Microsoft Learn

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