I spent most of my professional life in academic settings. It is not surprising, then, that I’ve partially been indoctrinated into the quantitative perspective. Nothing matters unless it can be reduced to observable numbers. These representations of reality seem to tap irreducable truth in some unbiased manner. Forget the inconvenient reality that quantitative figures can be manipulated in so many arcane ways and remain inscrutable to the mere mortals who constitute the hoi poloi. They seem inviolable.

I was thinking about this recently as I reflected on how some of the early titans of social media (Zuckerberg, Dorsey, Sandberg, and Theil) have so easily been sucked into the quant perspective. It is a path easily followed. I did it early in my career as I became enamored by catchy planning tactics like Management by Objectives and a host of derivative tools. Pick the right goal, formulate that end as a defined metric, then measure it to death. Running your company or government then becomes an easy task, or appears to at least. You then manipulate things to optimize that outcome.

I like to think of the adherents to this perspective as the brittle bright crowd. They are great at solving complex engineering and computer programming challenges. At the same time, they fall short when attempting to achieve the status of Plato’s philosopher kings. The lure of rigorous analytics fails to embrace the human dimension. Alas, technical acumen is not the same thing as wisdom. How I wish it were.

I am pushed to consider this topic by several books in which I’ve immersed myself of late. They tap a growing concern that the social media empire (Facebook, Twitter or X, Tic Toc, Snapchat, Instagram, et. al.) has led society into a dystopian nightmare where our youth is anxious, detached, depressed, and even suicidal; our politics are polarized and divided beyond repair; and our social fabric and communal identity is being ripped asunder.

How did that happen? Like many questions, at least one answer is easy to discern. As smart phones have taken over our lives, the social media platforms they provide us 24/7 now exert unparalleled influence over how we see the world about us. Moreover, there is a common business model behind all of these connectivity instruments and technologies.

The prime outcome of interest is engagement … the amount of time a consumer spends on a social media site. Learning, bonding, communicating, and all other possible positive outcomes implicitly associated with these technologies mean nothing. Only engagement counts since that factor appeals to those purchasing advertising. The more people on a site, and the longer they stay, the greater opportunity for the sellers of nonsense to peddle their wares. And when a platform is dealing with upwards of $80 billion in annual advertising, all else, including any concern with perverse consequences, quickly falls by the wayside.

Of course, these contemporary entrepreneurial gurus did not invent modern management. As far back as I can recall, there had been a push to introduce more rigor into government and the private sector. My own career was a testament to both the allure of the quant approach to things and the inherent pitfalls associated with it. This will be a mercifully quick tour.

Some of you will remember Robert MacNamara and the body counts in Vietnam. Robert had a reputation as a whizz kid, a new kind of corporate manager in the auto industry who would rely upon numbers and not ‘feel’ or ‘experience’ when making key decisions. When he took over as Lyndon Johnson’s Defense Secretary in the 1960s, he brought his corporate culture with him to Washington. His primary challenge at the time involved choosing a key outcome to assess success in the emerging Vietnam war, a conflict with no front lines and where winning battles had little meaning. But you could measure dead bodies. That seemed easily quantifiable. If you killed more of them than they did of you, you would win … no? Poor Robert eventually would admit his errors and that the war has been a tragic mistake. His misguided early hubris haunted him for the remainder of his life.

My early experiences in state government taught me several lifelong lessons, though on a less tragic level. One of my first responsibilities was to serve as the analyst for the state of Wisconsin’s Quality Control system (QC) for cash assistance for vulnerable families. Basically, samples of welfare cases were drawn, and the accuracy of eligibility and payments were assessed. The state was to employ these results to improve the accuracy of welfare decisions through various corrective actions. Sounds perfect as an example of the new and hard-headed approach to governing.

What happened, though, was I soon stumbled on an easy way to reduce welfare errors. Forget about complex corrective action strategies, just simplify the rules. Cash welfare for families had been tailored to individual situations. The workers tried to adjust individual grants to the fiscal peculiarities a family faced. This was a noble attempt at case equity. But now, to reduce errors, we began to radically simplify those rules. Eventually, we would wind up with a flat grant where only family size mattered. Our rationale was simple, fewer decision points and there were fewer chances for error.

The other byword of the new management was efficiency. That would be another lure for us young Turks of that era. So, I quickly concluded we had to automate government (back in the early 1970s). Until I left for the University, another obsessive project of mine (and like-minded peers) was to conceptualize and develop what was known as the Computer Reporting Network or CRN. When up and running, workers in Wisconsin’s 72 counties would merely collect data from an applicant for assistance and enter it into a remote terminal. The actual decisions would be made by a computer in Madison for the major assistance programs … cash assistance, (then) Food Stamps, and Medicaid. It was extremely efficient since only one application needed to be completed, and human input (including error) was largely eliminated.

But one quickly learns that unintended consequences lurk everywhere. Automating welfare decisions meant that ALL discretionary decisions had to be eliminated. Every vague and opaque decision point had to be transformed into a binary choice. It was either this or that. No gray permitted.

Between QC and CRN, we would take out all the human contributions associated with dealing with vulnerable families. The new system had all the hallmarks of modern management. It was efficient, accurate, and resulted in minimal maintenance costs. But, as do all innovations, there were costs.

Horizontal equity was sacrificed, there was little relationship between what a family needed (given unique circumstances) and what they got. Also, the human element was removed. Agency workers became data collectors and little else. They no longer helped clients with non financial needs, which often were the important stuff. Finally, a uniform or flat grant became much easier to cut over time since benefits were less obviously tied to actual needs. Sure enough, benefit guarantees began falling over time. When I went to Washington to work on Clinton’s plan in the early 90s, I oft joked that ‘we better reform welfare soon or there would be nothing left to reform.‘

Let us segue back to the titans of social media. They are clearly members of the brittle- bright group, excellent at analytics but not so great on the wisdom gained through broad experience. In fact, Silicon Valley was known to be populated by twenty-somethings during the heady days of the rise of social media.

These kids had an engineering mentality. They saw a problem and went after THE solution. Hard numbers were always at the heart of these solutions, and optimizing equations and algorithms paved the way. You know the drill … pick an outcome and make choices that maximized that number. In the end, they highly simplified their world. Work up the emotional state of the customer by leading them deeper into controversial (even dishonest) content since that enhances engagement and increases advertising revenues (i.e., profits.)

Many of these titans had fooled themselves, believing they were contributing to a new world based on universal communication. This was a world first intimated by Pierre Teilhard de Chardin some 75 years ago. In truth, they were trapped in a classic version of the prisoner’s dilemma associated with any investment initiative involving venture capitalists. They had to keep pleasing advertisers and thus increasing revenue streams. If they did the right thing for the public good, competitors would catch up. There was no way out of the trap they were in, no matter the costs to people and society.

Those costs are proving to be extraordinary high and show no sign of abating. A dystopian future seems inevitable at the moment. But their intentions were good, as were mine, back in my early days.