IT’S YOUR DATA, AND THIS IS YOUR BLOG

Welcome to the Collibra Blog, where CDOs, data stewards, and data citizens go to learn about true data governance.

subscribe

AI and Data Governance: Humans (Still) Need to Apply

Share: Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedInEmail this to someone

AI and Data Governance: Humans (Still) Need to ApplyIn history, we’ve seen three major eras in the automation journey of companies. In the first era of automation, machines relieved humans of work that was manually exhausting and mentally enervating. The second era of automation took on mainly grunt work, but stopped short of decision-making. Today, we are entering the third era of automation, where automation is gaining (artificial) intelligence. And in fact, it’s been proven that artificial intelligence – in various settings – is capable of making better decisions than humans.

Various opinions exist as to whether or not this third era will lead to job loss or not. But in the recent book ‘Only Humans Need Apply,’ authors Thomas H. Davenport and Julia Kirby argue that artificial intelligence (AI) will mainly augment knowledge workers rather than replace them and that people’s roles will simply change. While today’s automated systems are typically designed to do one thing very well, a major advantage human brain still enjoys over automated system is its breadth – the ability to do many things fairly well.

Furthermore, the book outlines several strategies to help workers stay relevant in a world where AI is introduced in the workplace. While the strategies below are considered “mutually exclusive” in their definition, often they are combined in individuals’ careers.

  • Stepping up: Focusing on big-picture insights and decisions that are too unstructured and sweeping for a computer to make.
  • Stepping Aside: Moving to a non-decision-oriented work such as selling, motivating people, or describing in human language what decision the computer made.
  • Stepping In: Engaging with automation to understand, monitor, and improve the systems.
  • Stepping Narrowly: Finding a ‘niche’ area where automation doesn’t make economic sense.
  • Stepping Forward: Developing the new systems and technology in the first place.

Clearly, artificial intelligence cannot exist (or be developed) without the availability of data. Exactly this data (and lots of it), and the ability to use it, has been one of the reasons for the recent acceleration in artificial intelligence. In fact, a paper by Royal Society recently highlighted the need for better data governance frameworks to further enable technology advancements.

But even once AI is introduced in the workplace, data – and data governance – play an important role in the ability to progress, explain, and grow.

The most obvious case is in the ‘stepping forward’ scenario where data is needed for day-to-day operations and activities. Data that should be available and governed, I would argue. But even in the case of ‘stepping in’ or ‘stepping aside,’ the information and decisions made by the machine should be governed and explainable as part of the information governance program.

Just how long will machines require human augmentation? We shouldn’t worry about that as long as machines are not able to tell they are doing a bad job and should be replace by a ‘better machine.’ This is an ability that is currently only available to human beings (until enough data exists to prove otherwise?)

 

Benedict is a Sales Engineer focused on the Financial Services industry. Before joining Collibra, he worked for Wolters Kluwer Financial Services as principal consultant implementing Finance, Risk and Regulatory compliance solutions worldwide.