Posts
Andy Cotgreave, senior director at Tableau Software, discussing how to practice good data governance to breed trustworthy and transparent AI.
How can organisations embrace AI ethically?
he A-level and GCSE exams fiasco exposes the significant problems in using algorithms to make complicated, life-changing decisions. As we rely more on AI and automation, “smart” systems are as likely to create as many problems as they solve. AI is not all bad nor will recent problems pause its growth, rather organisations continue to hit the accelerator on AI technologies on the promise of rapid delivery of value.
So, does a fast percolation of AI technologies throughout business and public sector bodies mean we can dispose of the human talent in their analytics teams? No. Experience shows people can comfortably integrate new technologies into their jobs and lives; AI and automation are no exception. AI, through appropriate algorithm usage, does have the potential to help us make better decisions in the workplace.
Embracing AI technology requires organisations to understand, from the top down, how their data and algorithms work. Human oversight is needed to avoid mistakes and ensure decisions are ethical...
Data governance: building AI integrity with data
Data professionals can play a pivotal role in making AI ethical and therefore of value. Let’s cut through the thick hype that wraps around AI and remember that garbage inputs will create garbage outputs.
Rigorous data governance is foundational for successful AI implementations. Quite simply if you don’t have good oversight of the data in your organisation that’s used to train AI or given to an AI to analyse, you always risk inaccurate outputs and decisions.
Source: Information Age
