As companies accelerate their use of AI and autonomous systems—technologies that are fueled by data and extract meaning from data—the importance of information governance escalates as well. What data does the business seek to use or generate? Is the data real or fake? Is it reliable? Biased? Is it being used effectively for the intended purpose? Is that use ethical? Further, what private stories might aggregated data uncover? And importantly: who in the organization has the responsibility for and competence to answer such questions?
Adoption and implementation of AI systems requires knowledge and process. This course seeks to augment the understanding of AI systems for information governance professionals and others engaged in the protection or use of corporate data. The course also addresses accountability for meeting the social, ethical, and legal obligations of a company—which after all, operates under a privilege that is granted, not inherent. Gaps in process and accountability for corporate reliance on the patterns the AI systems identify present a leadership opportunity to information governance professionals, who can bring an important voice to the conversation. What should information governance professionals know about data and AI systems and their impact to fully support the business?
Learning objectives
- Understand how AI and autonomous systems interact with data
- Understand the components of an effective workflow for training, monitoring, and calibrating AI systems
- Recognize issues of data bias, integrity, and ethics in AI systems
- Recognize the importance of ethics oversight in corporate use of AI systems
- Understand how information governance professionals can take the lead in constructing a governance system for use of AI systems
- Understand how to foster the important communication needed among stakeholders