How Good Should Institutional Memory be? - Reframing (Digital) Identity Systems as Institutional Memory

Contemporary institutions and record keeping systems using paper co-arose. Institutions created systems to track interactions with people over time, creating a form of institutional memory by using a range of paper-based technologies such as file record keeping and index card systems. Over the last 60 years, digital identity systems have emerged and continue to improve, thus accelerating the capacity of organizations to form institutional memories. Now we have the emergence of AI and machine learning that will advance this further - making super institutional memory.

This session explores a reframe of seeing digital identity systems as institutional memory and considers re-framing the question as how good we want institutional memory to be when building identity systems. This could be a resolution to the race between companies, partially driven by surveillance capitalism, to collect data and regulatory bodies imposing laws and regulations on data collection in the name of “privacy”, some of which have not adjusted for new technology. These two drives are inherently in tension with each other.

Asking "how good should institutional memory be'' transcends these two different drives and shifts the challenge of data collection out of a "corporate alone" decision or responsibility. It also invites a broader conversation with the public who interact with institutions and policy makers that regulate them. The answers to this question may be different for different types of institutions, but they can create new norms that bring different sides together to figure out how things should work and understand trade-offs and limits in new technologies such as decentralized identity.