Trust vs. Surveillance Cultures
Year 2120, Month 6, Day 10 — Mars Colony, Goddard Station — I was busy debugging a tricky error in a deep space telemetry optimization module when I got a ping from PAPA. The Performance Assessment & Productivity Algorithm has been in place since forever, to the point you almost forget about it. Until it pops up from the holovisor unexpectedly.
“Hello Lawrence,” PAPA sounds like one of those old Earth Mid-America male accents.
“Yes?” I wearily reply. Why does PAPA’s tone always feel like a schoolyard scolding?
“I was noticing that your email responsiveness metrics have dipped below the optimal 82% threshold. I have provided a remediation strategy in your holomail.” More holos. Great.
“Yes PAPA, anything else or can I get back to work now?” I mutter as I return to my setcon.
“Well in fact, there is something else. It has to do with your MindStat scores. We have detected three straight days of below threshold emotional quotient marks. Is there something that we should be aware of?”
“Ah, what you are getting at?” I respond, putting on my poker face.
“There is an obvious deviance from historical data. We suspect this has to do with growing unease with your current assignment. Blood toxicity reports and posture readings show strong evidence of excessive consumption of banned alcoholic substances, and…”
“Why don’t you shove your evidence up your circuit board!” Oh no…losing my cool.
“It is clear that this situation is causing defensiveness and anxiety. You are required to see MAMA (Mental Adjustment & Management Application) at 16:20 for a full neural scan and evaluation…”
By the end of 2021, one billion cameras will be watching us. That is according to IHS Markit and includes government owned cameras as well as CCTV in private businesses that opt to connect to police networks. That is not just in places like China either. The growth in cameras in the US and elsewhere is skyrocketing.
The growth is driven by advances in analytics and AI that make the explosion in feeds and data manageable. AI is also surfacing deeper insights by identifying objects, distinguishing human faces, and determining intent based on historical context, setting, and behaviors. The fears raised by the misuse of AI led IBM to recently end the sale of its facial recognition technology.
Most of the concern about surveillance technology has been on its public use, especially now given the protests erupting across the US. Surveillance tech however has been quietly gaining traction in the workplace well before COVID-19 and work from home ignited the discussion. Last October for example, Outback Steakhouse had to backtrack on a pilot that used cameras and AI to monitor workers in real time. That still has not stopped Domino’s Pizza from deploying their “pizza checker”, which is essentially the same thing.
Maybe one can dismiss the fast food industry and their march towards automation. Fast food as always had a conveyor belt, assembly line vibe to their operations, which has enabled the industry to scale and keep costs low. It is not so hard to imagine the KFC and McDonald’s of the future all staffed by robots. Robots are already making pizza.
Knowledge professionals have largely avoided such intrusions into monitoring their work. While most of us have experienced the overbearing micromanager that creeps over our work area to “check-in”, knowledge workers still have the space and freedom to manage their own time.
Then COVID-19 forced companies to go into full remote work mode. For IT teams, this meant scrambling for bandwidth, equipment, and remote access tech. For legal, compliance and risk teams, this meant scrambling for ways to ensure information was not being leaked. For many managers, this meant finding ways to make sure their staff was not goofing off.
The technology for monitoring office workers is not new. For years, there have been things like keystroke tracking, Internet and email usage monitoring, document access detection, and the use of cameras and security cards to watch the comings and goings of employees. A new era of SaaS tools has gone farther by enabling location tracking and automatically taking screenshots and recording webcam videos throughout the day.
The challenge with any of these tools however is the needle in a haystack problem. Within the millions of datapoints captured, how do employers spot non-compliant behavior? This is where AI has significantly advanced the state of art in surveillance.
Machine learning has now reached a stage of maturity where it can analyze human work and determine a “productivity score”. As the CEO of one company explains, the technology is supposely helping employees:
“Imagine you’re managing somebody and you could stand & watch them all day long, and give them recommendations on how to do their job better”
The justification seems rational from a corporate perspective. Leadership is always attracted to ideas and methods that can optimize the business and improve results. There is a thirst for data sets that uncover hidden cost and productivity savings. As Eva-Sage Gavin of Accenture states:
“Overall, 77% of business leaders say new sources of workforce data will help them grow their business, 76% say it will help them transform the business for agility and efficiency, and 74% say it will help unlock the full potential of their people.”
As well-intentioned monitoring may sound however, the idea of AI acting as an arbiter of our workplace productivity is disturbing. It takes the worst elements of the manager from hell and weaponizes the inhumanity, creating a workplace where nothing but activity matters and pits managers against their employees. If you think my vignette from before was just fanciful fiction, the technology to enable that level of monitoring exists today.
There are plenty of organizations that are willingly taking the plunge into overt monitoring. On the Westrum scale, they fall under the pathological or bureaucratic end of the scale where command and control management tactics are dominant and trust in other people and teams is low to non-existent. What is valued in this environment are inputs (hours worked, emails sent, lines of code written), adherence to process, and survival skills to navigate the corporate political grinder.
Contrast those organizations with those that are generative. Trust is the currency and a shared value, which leads to greater sharing, higher productivity, and faster innovation. When they hire employees, managers give them the agency to make decisions and the trust to experiment, fail, and learn. Employees are naturally motivated to succeed and to support the mission.
Organizations have a choice to make in this pivotal moment. Will they choose to become a surveillance culture or a trust culture? Or more fundamentally, do they believe employees can be self-motivated to do great work, or do they feel knowledge work is the equivalent of pizza robots?
There are people taking a public stance against this move towards unfettered monitoring. I will leave you with this tweet from DHH of Basecamp on his views on the topic:
What is your company’s stance on surveillance technology? Do you believe monitoring can be used in ways that can be helpful for employees?
Episode #11 — New ways of working and managing through agility with Rob England
New episode of the Heretechs podcast is here! Co-hosts Justin Arbuckle and Mark Birch welcome guest Rob England, the Founder of Teal Unicorn and the blogger formerly known as The IT Skeptic, to discuss what has changed in the nature of our work and how to navigate that change with agility.
We help IT leaders in enterprises solve the cultural challenges involved in digital transformation and move towards a community based culture that delivers innovation and customer value faster. Learn more about our work here.