AI and data are subjects raging everywhere these days, and oftentimes, the data collected and collated by AI is being turned into metrics. Nowhere is this more evident than in productivity and collaboration solutions.

These solutions are now tracking who you contact, how often, how long, and present this information to your manager with colorful graphs and an easy dashboard.

More disturbingly, some of these packages can even monitor speech for forbidden words or phrases. They can also make suggestions on following up on emails, tasks and other things in your inbox.

AI driven defaults may fail

It will take next to no time for an unscrupulous employer or even a clueless one to begin to use these AI-driven data sources to try and increase employee productivity. The flaw here mostly isn’t the capitalistic desire to increase output, it’s in the knock-on effects and human factor that will make many of these efforts counter-productive.

First, default productivity ideas, such as how much you should or should not contact your co-workers is highly specific to your industry and job environment. Following the defaults, which is what most will do, is not likely to lead the improvements they are looking for. But that’s just the tip of the iceberg.

Metrics may for a change in behaviour

The second issue is really with people. Much of the basis for our productivity metrics come from factory environments, where things like units per hour, repetitive movement counts, and restock/reset times can all help management determine how to make improvements on the factory floor.

The problem is taking this philosophy and applying it to office and knowledge workers. The “factory production line” mentality leads to negative or at least unpredictable outcomes. Metrics are a fact of business, but when the metrics get too personal or too pervasive, there is a noticeable shift in human behaviour.

Instead of working to do the job well, employees work to the metrics setting aside the greater good for the customer and company to improve numbers. Ask anyone who has worked long term in a heavy-metrics based environment, the metrics become the raison d’etre, taking on a life of their own. Everything looks great according to the metrics, but the business and process suffers.

Trust and dignity

The ease in which these metrics can be obtained and used is also an issue. These products are being marketed to management, showcasing colorful dashboard and productivity indictors. While there is nothing wrong with that, the reality is that implementing these metrics is a decision that needs careful consideration and planning and frequent re-visiting.

The other issue from a human standpoint is one of trust and dignity. The amount of data that can be gleaned from a single employee is going to do nothing but increase. Every word, movement and keystroke can be recorded and turned into metrics. Employment requires a certain level of trust between both parties. Even more disturbing is AI technology that listens to every call and every meeting, flagging keywords and alerting management when a forbidden word is uttered.

Heavy AI-driven metrics, listening, and scoring takes on a dystopian quality normally reserved for cyberpunk fiction. How rigid and how invasive these metrics are will become a basis for employees to judge what a good employer is.

Many of these metrics will prove useful to both employer and employee, but only if they are implemented transparently and with ethical guidance and the attitude that individuals working for a company are not machines to be tuned for maximum company performance. If companies go too far in these early days of AI-driven data collection, the public will demand laws banning it, a result that benefits no one.