All Posts by Bob Lewis

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Before we get started, a correction. Last week, due to too many re-writes, I ended up posting backward logic, as several correspondents pointed out. You’ll find a corrected version here, near the bottom, in the Bob’s Last Word segment.

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Speaking of bad metrics (we weren’t, but I couldn’t come up with a better segue to this week’s topic), let me offer a big thank-you to Lee Neville, a long-time member of the KJR community, for bringing a high-profile example to our attention.

Titled “At N.F.L. Draft, America Begins Annual Tradition of Celebrating Hubris,” it’s by David Leonhardt and appeared in The New York Times, April 28, 2022. Annoyingly enough, I’m pretty sure Leonhardt’s core conclusion is at least partially on target: with lots at stake, and huge investments in data-gathering and analysis, the correlation between NFL draft rankings and player performance isn’t very good.

Leonhardt ascribes the problem to hubris, and extrapolates his conclusion to business hiring, which he suspects is just as unreliable, and for similar reasons.

So what’s the problem? Leonhardt bases his conclusion on the five 2018 first-round quarterback draft picks. Using career touchdowns as his metric, he demonstrates conclusively that actual career performance and draft order have little to do with each other.

I’m just messin’ with you. He did no such thing.

The illogic of his commentary began with his choice of career touchdowns as his quarterback performance metric. It conceals a wealth of missing but important information that’s critical to evaluating Leonhardt’s contention. For example:

Did all five quarterbacks play the same number of games? The answer is no. Baker Mayfield, for example, didn’t play until partway through week three of the 2018 season. In all he’s played 60 games, Sam Darnold has played 50. Josh Allen … the quarterback with the most touchdowns has, suggestively, played the most games at 61. That leaves Josh Rosen having played 24 games and Lamar Jackson 58.

It doesn’t take a metrics nerd to know that playing in fewer games means having fewer opportunities to score touchdowns.

Did all five of these quarterbacks enjoy the same level of protection? Every football fan knows that the better the offensive line, the more time the quarterback has to execute plays and the more successful he’ll be.

And yet, with all the zillions of statistics football game callers give us to fill time as part of their commentary, nobody seems to measure the average time between the snap and the moment the quarterback throws the ball or is sacked (limiting analysis to passing plays only for clarity). A similar point could be made about the caliber of the team’s receivers and running backs.

ESPN take note.

How about the quality of coaching? While some quarterbacks do call some plays, the coaching staff create the game plan and call a lot of the plays as well. Presumably, some coaches are better at this than others, which means some quarterbacks are the beneficiaries of better game plans and play calling than others.

A sample size of five? Seriously? With all the data available for football, getting to the magic number of 30 data points – the minimum needed for general-purpose statistics – wouldn’t have been all that difficult. Statistically speaking, a sample size of five is just pretending, especially because … why choose the 2018 draft for analysis and not some other year, anyway?

Bob’s last word: Picking on Leonhardt is fun, but it isn’t entirely fair. Far too many of his fellow reporters and opinion writers of all stripes just aren’t very good with math or statistics either, whether they cover sports, politics, management, or information technology. We can hope the level of sophistication among journalists who cover the fields of math and statistics is better.

Then there’s Leonhardt’s conclusion – that recruiting in all fields is a matter of hubris. It would be convincing if he offered a better alternative. So yes, recruiting and selecting the best candidates to hire is an imperfect science at best. That doesn’t mean a high failure rate is due to character flaws all around.

It means it’s hard.

Bob’s sales pitch: Schrodinger’s cat is alive and well, as will be revealed on May 11th, 2:40pm CST. That’s when a battle royale will ensue, as I engage with the estimable Roger Grimes in The Great Quantum Debate: Is There a Role in Business Yet? as part of CIO’s Future of Data Summit.

Oh, okay, it won’t be a battle royale, but there’s a pretty good chance you’ll enjoy it almost as much as Roger, Eric Knorr – our moderator – and I did when we recorded it.

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There once was a feller named Elon

For Twitter he just made a deal on

Is he free speech’s savior

Or is his behavior

Just something we’ll never agree on?

Social media are the best source of accurate news for Russians trying to understand what’s really going on in Ukraine.

Social media are also the best source of utterly false propaganda for Americans looking for talking points about the conflict in Ukraine they can use to justify their admiration for Vladmir Putin.

Before we get all worked up about Elon Musk’s Twitter acquisition and plans to take it private, let’s take a deep breath and de-murkify some aspects of the situation that, to my lay-person’s eyes at least, are in desperate need of de-murkification.

Does Twitter engage in censorship?

No. Censorship is something governments do. Twitter is a business, not a government.

Does Twitter currently engage in excessive editorial control?

This isn’t a yes-no question. It’s a how-much question.

The more editorial control Twitter exerts over the content published on it, the more it resembles a publisher rather than a platform. Oversimplifying, publishers are responsible for the content they publish. Platforms aren’t responsible for the content published on them. But it’s a continuum, not a binary categorization.

Twitter exerts some editorial control over the content posted on it (see The Twitter rules: safety, privacy, authenticity, and more ).

That control doesn’t extend to requiring that what’s posted on it is true, though, so to my eyes it’s still more platform than publisher. Your retinas might reach a different conclusion.

Do government efforts to regulate Twitter’s content constitute censorship?

That depends which content.

Content posted by individual human beings is, and (in my not-very-humble opinion) should be protected by the First Amendment. This also means it’s governed by the First Amendment’s well-established boundaries. Defamation, endangerment, and incitement to violence are as illegal on Twitter as when yelled out by an angry person standing on a soapbox in Central Park.

Content posted by corporations, in contrast, isn’t (or at least, shouldn’t be) protected by the First Amendment. Supreme Court rulings that “corporations are people too” notwithstanding, that’s still a legal fiction. Everything corporations do is legally subject to regulation, because forming a corporation is a privilege, not a right.

The most obvious and clear-cut example of legitimate regulation of corporate speech is false advertising. A company that publishes falsehoods about its products is violating the law.

As for content posted by ‘bots, ‘bots aren’t persons. They have no constitutional rights of any kind, whether deployed by corporations, governments, or autonomously (a terrifying thought).

Does government regulation of “the algorithm” constitute censorship?

No, and with all due deference to the late, great Frank Zappa, this, not the apostrophe, is the crux of the biscuit.

First of all, the technology social media concerns use is the polar opposite of an algorithm. Algorithms apply known rules to turn their inputs into outputs. Social media use neural networks, and as is well known, even the neural networks themselves don’t “know” how they reach their conclusions.

Social media neural networks are, that is, both autonomous and oblivious. Not a good combination.

Of greater significance, the act of deciding which content to bring to subscribers’ attention, whether it’s through the use of true algorithms, neural network “algorithms,” or an editorial committee composed of actual human beings, pushes social media like Twitter and Facebook closer to the publisher end of the platform / publisher continuum.

How about Section 230?

Section 230 was an attempt to define any and all internet services that democratize content creation as platforms. It was crafted in a simpler, algorithm-free time (1996) and needs replacing. Finding even two people who agree on what to replace it with, though, is a challenge.

Bob’s last word: If I was a predicting kind of guy, I’d go along with everyone else commenting about this subject: Musk will take a laissez faire approach to editorial control, including but not limited to removing restrictions on who is allowed to publish on Twitter.

Corrected from the original:

That would move it much closer to being publisher than platform.

And Musk will have a hard enough time keeping that from happening without tearing out the so-called algorithms Tweetsters rely on to decide what to pay attention to and what to ignore.

That would move it closer to being platform than publisher.

But Musk will have a hard time maintaining platform status without tearing out the so-called algorithms Tweetsters rely on to decide what to pay attention to and what to ignore.

If past behavior predicts future grousing, Musk won’t have much patience with the legal need to thread this metaphorical needle.

Bob’s sales pitch: Reserve May 11th, 2:40pm CST, when I engage with the estimable Roger Grimes in The Great Quantum Debate: Is There a Role in Business Yet? as part of CIO’s Future of Data Summit. You can register for the summit here. I predict you’ll find it even more informative than your average Tweet.

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