About the Conference
November 19, 2020 – November 20, 2020
Machine learning and artificial intelligence algorithms promise many benefits such as overcoming human limitations and biases in decision-making and productivity. However, deployment of machine learning algorithms has shown that these algorithms may amplify existing biases in society, create new biases, increase privacy and cybersecurity risks, and pose novel ethical dilemmas.
The conference will explore how society and organizations can maximize the benefits and minimize the risks of these algorithms.
Specifically the conference will focus on the multi-dimensional nature of algorithmic risks and biases with speakers and panelists who are experts in the respective dimensions:
- Legal and economics scholars and practitioners who will discuss how laws and regulations can foster algorithmic accountability and fairness
- Organizational scholars and practitioners who will discuss how organizational governance and control mechanisms can mitigate algorithmic risks and biases
- Computer science and data science scholars and practitioners who will discuss how their professions can foster ethical, responsible algorithm development approaches
- Social-psychological scholars and practitioners who will discuss how individual-level awareness about pre-existing, implicit biases can be increased to foster ethical and responsible uses of algorithms.