This post has been republished via RSS; it originally appeared at: Microsoft Tech Community - Latest Blogs - .
Advancements in AI technology have simplified the way we accomplish many tasks, allowing us to do things we once thought impossible. With the growing number of AI enthusiasts acquiring new skills and staying updated with the latest developments, it's expected that innovative solutions will keep surfacing globally. This progress will empower a larger audience to accomplish a broader range of activities.
The swift advancements in AI are transforming society significantly, but they also bring potential risks. While AI is designed to aid in the success of a broad audience, it could have unintended negative effects. It's crucial for organizations, developers, and users to adopt a responsible approach and proper understanding of AI to ensure it benefits society as a whole.
Therefore, the idea of "Responsible AI" refers to essential rules that everyone working with AI should follow. Brad Smith, Microsoft's Vice Chair and President, mentioned in an article that since 2017, Microsoft has committed to these rules, focusing on six key areas: Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, and Accountability. Ensuring AI treats everyone fairly, works reliably and safely, protects privacy and security, includes everyone, is transparent, and holds those involved accountable for their creations. This approach helps make AI beneficial and trustworthy for all.
Veronika Kolesnikova, an AI MVP, actively disseminates her technical expertise and insights on AI technology through her community involvement. This blog post aims to present her concepts and viewpoints to assist those interested in gaining a deeper understanding of responsible AI practices.
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Please tell us details about your recent community activities focusing on responsible AI.
I was talking about responsible AI and Content Safety at the Hack Together virtual event. The event was a hackathon with Live virtual presentations. I had my session on February 9th and although it was less than an hour long I was able to talk about responsible AI principles, Content Safety and show a demo on how to set up custom content filter inside Azure OpenAI Studio.
What do you suggest AI users to be aware of when using generative AI in terms of responsible AI?
I like reminding people that AI is not a magic box and only processes data you’re sharing with it, whether it’s though input or training data. Humans have to be accountable for AI systems: make sure training data is accurate and clean, each change has an author and there’s always a switch off “button”.
As a community leader, how do you help community members who would like to learn more about responsible AI?
If I find something worth checking out online, including online learning opportunities, interesting tools and approaches and blogs/books, I always share it with the community through social media. Sharing experiences, learning from others, and educating yourself on principles and news about responsible AI is very valuable for everyone.
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The more AI becomes familiar and accessible to many people, the more important it becomes for each individual to learn about responsible AI and to think about its proper development and use. Veronika has also shared insights on this point. “AI is hue right now, it’s everywhere, so even if people are not building AI-based software or custom ML models, they still need to understand Responsible AI principles and apply them to the daily life whenever they’re using AI.”
To deepen your understanding of responsible AI, consider exploring these resources. Your unique ideas can contribute to the development and implementation of cutting-edge AI solutions globally. It's essential to have a thorough grasp of both AI technology and the principles of responsible AI to drive innovation responsibly.
- 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
… and more!