The Health Pulse S2E5: Creating a Healthier World with Ethical AI
On this episode, Greg catches up colleague Reggie Townsend, director of the Data Ethics Practice at SAS. Recognizing the increasing market need around data ethics, SAS formed the practice to establish principles and processes for governing Artificial Intelligence (AI). The practice applies a human-centric approach to upholding principles such as transparency, accountability and inclusivity in data science. Townsend challenges his team to start by considering the impact of technology on the most vulnerable populations. Understanding bias plays an imperative role in AI ethics. For example, Black neighborhoods in the US, like the one where Townsend grew up in Chicago, are more likely to be food deserts. The people in those communities lack access to healthy food and have poorer health outcomes as a result. When evaluating health data, it is critical to understand the facts and historical context behind the data in order to deliver effective decisions and solutions that are free of bias. Looking forward, Townsend is hopeful that the ethical development and deployment of AI-related technology can lead to brighter futures for all people.
On this episode, Greg catches up colleague Reggie Townsend, director of the Data Ethics Practice at SAS. Recognizing the increasing market need around data ethics, SAS formed the practice to establish principles and processes for governing Artificial Intelligence (AI). Townsend defines AI as an algorithm or set of instructions given to a computer for decision making. He explains that the market definition of AI is now the entire analytics life cycle from the initial ingestion of data through to analytic modeling, data visualization and the decisions that are ultimately made. While examples of unethical AI, such as discriminatory hiring and lending practices, necessarily get a lot of attention, there are many more examples where AI is used to our benefit. Data science is deployed to optimize many aspects of daily life from our banking experience to flight routes to recommendation engines.
SAS’ Data Ethics Practice applies a human-centric approach to upholding principles such as transparency, accountability and inclusivity in data science. Townsend challenges his team to start by considering the impact of technology on the most vulnerable populations. Understanding bias plays an imperative role. For example, Black neighborhoods in the US, like the one where Townsend grew up in Chicago, are more likely to be food deserts. The people in those communities lack access to healthy food and have poorer health outcomes as a result. When evaluating health data, it is critical to understand the facts and historical context behind the data in order to deliver effective decisions and solutions that are free of bias. Looking forward, Townsend is hopeful that the ethical development and deployment of AI-related technology can lead to brighter futures for all people.
A transcript of this episode can be found here.
All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.
SAS’ Data Ethics Practice applies a human-centric approach to upholding principles such as transparency, accountability and inclusivity in data science. Townsend challenges his team to start by considering the impact of technology on the most vulnerable populations. Understanding bias plays an imperative role. For example, Black neighborhoods in the US, like the one where Townsend grew up in Chicago, are more likely to be food deserts. The people in those communities lack access to healthy food and have poorer health outcomes as a result. When evaluating health data, it is critical to understand the facts and historical context behind the data in order to deliver effective decisions and solutions that are free of bias. Looking forward, Townsend is hopeful that the ethical development and deployment of AI-related technology can lead to brighter futures for all people.
A transcript of this episode can be found here.
All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.
