Artificial Intelligence is clearly a powerful tool that could help a number of sustainability objectives, but are there risks attached to these potential benefits? Global Head of Sustainability Research Stephen Byrd and Global Sustainability Analyst Brenda Duverce discuss.----- Transcript -----Stephen Byrd: Welcome to Thoughts on the Market. I'm Stephen Bryd, Morgan Stanley's Global Head of Sustainability Research. Brenda Duverce: And I'm Brenda Duverce from the Global Sustainability Team. Stephen Byrd: On the special episode of the podcast, we'll discuss some key A.I. related opportunities and risks through the lens of sustainability. It's Friday, April 14th at 10 a.m. in New York. Stephen Byrd: Recent developments in A.I. make it clear it's a very powerful tool that can help achieve a great number of sustainability objectives. So, Brenda, can you maybe start by walking us through some of the potential benefits and opportunities from A.I. that can drive improved financial performance for companies? Brenda Duverce: Sure, we think A.I. can have tremendous benefits to our society and we are excited about the potential A.I. can have in reducing the harm to our environment and enhancing people's lives. To share a couple of examples from our research, we are excited on what A.I. can do in improving biodiversity protection and conservation. Specifically on how A.I. can improve the accuracy and efficiency of monitoring, helping us better understand biodiversity loss and support decision making and policy design. Overall, we think A.I. can help us more efficiently identify areas for urgent conservation and provide us with the tools to make more informed decisions. Another example is what we see A.I. can do in improving education outcomes, particularly in under-resourced areas. We think A.I. can help enhance teaching and learning outcomes, improve assessment practices, increase accessibility and make institutions more operationally efficient. Which then goes into financial implications A.I. can have in improving margins and reducing costs for organizations. Essentially, we view A.I. as a deflationary technology for many organizations. So Stephen, the Morgan Stanley's Sustainability Team has also done some recent work around the future of food. What role will A.I. play in agriculture in particular? Stephen Byrd: Yeah, we're especially excited about what A.I could do in the agriculture sector. So we think about A.I. enabled tools that will help farmers improve efficiencies while also improving the quantity and quality of crop production. For example, there's technology that annotates camera images to differentiate between weeds and crops at the pixel level and then uses that information to administer pesticides only to weed infested areas. The result is the farmer saves money on pesticides, while also improving agricultural production and enhancing biodiversity by reducing damage to the ecosystem. Brenda Duverce: But there are also risks and negative implications that ESG investors need to consider in exploring A.I. driven opportunities. How should investors think about these? Stephen Byrd: You know, we've been getting a lot of questions from ESG investors around some of the risks related to A.I., and there certainly are quite a few to consider. One big category of risk would be bias, and in the note, we lay out a series of different types of bias risks that we see with A.I. One example would be data selection bias, another would be algorithmic bias, and then lastly, human bias. Just as an example on human bias, this bias would occur when the people developing and training the algorithm introduce their own biases into the data or the algorithm itself. So this is a broad category that's gathered a lot of concern, and that's quite understandable. Another area would be data privacy and security. An example in the utility sector from a research entity focused on the power sector, they highlight that the data collected for A.I. technologies w