With the widespread use of generative AI applications and tools in the modern world, being proficient in implementing AI systems is not enough. As an AI product manager or a gen AI developer, you need to ensure that the system or tool that you developed is free from biases, privacy issues, ethical issues, as well as governance and compliance issues. As the number of AI-related incidents due to irresponsible use increased to 56.4%, it is crucial for companies to implement AI according to the ethics and ensure compliance. Using AI responsibly is pivotal for all organizations and industries, so the demand for AI product managers and responsible AI developers is constantly on the rise. However, as an AIPM or a product developer, it is vital for you to know all the nuances of implementing AI across the board and ensuring that it fulfills all the check boxes that adhere to the responsible use of AI.
Here are some responsibly used generative AI examples that companies have incorporated. Most importantly, how leading brands and multi-national companies have harnessed responsible AI principles that have made them successful. Most importantly, the companies were able to overcome several challenges and enhance their processes all while being compliant with the latest regulatory norms and ensuring that the AI was free from bias.
Microsoft’s Rigorous Ethical AI Practices
Microsoft implemented a rigorous AI ethics review process for nearly all AI products and features. They have implemented a fair usage policy for responsible AI use in the best ever method. With the help of their in-house team of gen AI developers, the company has undergone an audit that assessed the compliance with the responsible AI principles. These principles include fairness, safety, reliability, privacy, security, and inclusiveness as well.
The Microsoft teams developed their AI-powered chatbot in Microsoft Teams by collaborating with the AI product manager and the Responsible AI Ethics and Effects in Engineering and Research (AETHER committee) to look for potential risks in implementing the AI system and LLM model. This helped the team narrow down the potential of inappropriate content and how the internal tools were used to evaluate the model’s outputs for biases and other ethical considerations.
Google’s Equitable AI Research Roundtable
Google has been building quite a lot of AI-powered systems which have empowered them to scale up in operations in the best possible manner. In order for the tech giant to overcome challenges in following responsible AI practices, the company has founded a dedicated equitable AI research roundtable which comprises social scientists and industry experts from different domains. This enables AI product managers to get appropriate feedback on responsibility considerations for different products in the best possible manner. The team will be able to receive holistic product reviews for nuanced considerations of biases and regulatory considerations.
Salesforce’s Ethics by Design Model
As a leading software service provider, Salesforce gives the best products for their clients and strengthens its stakeholder relationship by reinforcing customer trust through their ethics by design model. This model has ethical considerations throughout the product development lifecycle, helping the client to conduct regular reviews of the AI tool. This helps Salesforce to meet various ethical standards and avoid causing unintentional harm. This has helped the Salesforce to better enhance their products and incorporate AI across various verticals seamlessly.
The way how these leading organizations have made responsible AI a part of their operations were seamless and fruitful in every way. AI product managers were able to clearly integrate AI applications and responsibly implement the system by adhering to the checklist. Once you become an expert in understanding all that you need to know about AI, you can start framing guidelines that promote the responsible use of AI according to the requirements of the organization or the client. However, it may be hard to implement the guidelines. That’s where Eduinx comes into the picture.
Conclusion
As a leading edtech institute that offers courses in generative AI and AI in product management, you can learn all that you need to know about the responsible use of AI through a hands-on approach. WIth guidance from non-academic mentors who have over a decade of experience, you can get the right guidance from them and understand responsible AI principles in a holistic manner. You can become a senior gen AI developer or an AI product manager with the right exposure through Edunix’s courses.
