I recently read a story about an airline worker being arrested for stealing thousands of dollars worth of goods from luggage at the airport. He got nabbed, thanks to Apple’s low-key tracker devices, AirTags. The very same AirTags have been the subject of stories (and inquiries) into “stalking” cases and other similar heinous maleficence. Of … Continue reading AirTags: what are they good for?
Nothing is more frustrating to me than YouTube, which decides my front page based on my likes. It seems I can’t have multiple interests — variables — and thus, I must watch certain kinds of videos. In its infinite wisdom, Twitter believes that only the people whose content I like or share are the ones whose content I want to consume. And don’t get me started on online dating services — they could learn a thing or two from Sima Taparia.
And that is because the post-social world of today is starting to coalesce around variables that are less humanistic and more biased towards corporate goals. “We live in a world that demands categorization,” I recently read in a newsletter, Tiny Revolutions. “We have to do some self-definition so the world knows what to do with us, and so that we can bond with others who share our interests, values, and concerns.”
While the writer, Sara Campbell, might have been talking about an individual’s desire not to be categorized, her words accurately describe our post-social society’s reality, dilemma, and futility in a handful of lines.
Categorization is part of the human condition. Our brain uses categories to help us make sense of a lot of facts we experience. It is how we learn. As humans, we need categories to contextualize our world, and that includes each other. What is more important is the intent behind the categories.
Categories, as such, have bias by intent. The bias allows us to ignore variables we don’t want to deal with and place boundaries around a category. It’s important because by ignoring them, we have to use fewer cognitive resources. The bias itself is not good or bad. It is the intent that leads you in different directions. That intent determines what variables we focus on and the ones we ‘choose’ to ignore.
And a lot of that intent is determined by the human condition. For example, if you have grown up in a more traditional society, the category that defines you is your lineage for most of your life. The “intent” of that categorization is to find your place in the social hierarchy. Lineage isn’t a primary variable for Americans, but college and money are. That is why in more modern societies, such as America, the college you attend defines your place in society and the workplace.
Ever wondered why most conversations start with a question: what do you do? That question is not only reflective of our fading art of conversation, and it also is a way for us to define the variables and get a quick context on the person. By doing so, we quickly decide to assign a value-metric to the person who is the recipient of our attention.
At best, in the pre-Internet world, categorization would rear its head in a social context, often giving us cues on how to engage with someone. An attractive single woman gets a different kind of attention from another woman versus a single man. Given the nature of modern consumerist society, it wasn’t a surprise that the emergence of databases allowed marketers to categorize us into “buckets” of those who may or may not buy some products. After all, the early usage of computers had been catalyzed by the demands from governmental agencies and corporations that wanted to use data to create categories.
However, in our post-social society, these categories have become even more granular and metastasized. Just take Facebook as an example. School, location, gender, relationships, and many more variables have started to create a profile of us that can be bundled no different than the dastardly collateralized debt obligation (CDO.)
And it isn’t just Facebook that is alone in using so many variables. From online dating services to online marketing to banking, most of them feel both antiseptic and plastic. These data variables are what make up an algorithm whose sole job is categorization. At present, the algorithms are relatively simplistic. They lack the rationality and nuance that comes from social science.
The bigger question is, what if all these data variables picked by companies for their own needs don’t define you or your interests. I suspect all of us be trapped in a data prison — forced to live lives that an invisible black box algorithm will decide what is good for us.
August 24, 2021, San Francisco
Seven years ago, when traveling to Italy, I experienced the vagaries of data and its weird, unimaginative influence on our lives. Since then, the absurdity of what data-driven intelligence throws at us on a daily basis has increased exponentially. I wrote about it in an essay, 40 kilometers. It was part of a series of essays I wrote about data, its implications, and the emergence of limited-intelligence algorithms. If you are interested, here are some links to those articles in my archives.
- Why data without a soul is meaningless
- With big data comes big responsibility.
- Uber, Data Darwinism and the future of work
Somehow that article, 40 kilometers, from seven years, ended up in the email inbox of my good friend Steve Crandall, who wrote a wonderful email reply in response. I thought it would be worth sharing and asked for his permission. Here it is:
The ‘data-driven world that we find all around us has little to do with science where data is highly contextualized and serendipity is welcomed and even hunted. I think the notion of art is will be, or at least should be, important.
Operating as a simple person I like to make a distinction between awe and wonder. Both have multiple definitions, so I use my own. Awe is a feeling of overwhelming majesty or even fear that seems to be beyond what we can understand or control. Wonder is a deep feeling of curiosity that leads to questions that can be addressed. It’s scale may be big or small, but it can be consuming at any scale.
Wonder is what I’m after and some of the paths have been decades long. As a student in Pasadena I’d go on a long bike ride down to one of the beaches with the cycling club once or twice a month. Being wasted from the ride and contemplating a more strenuous return I’d get lost watching gulls or the waves and surf. I’d wonder about waves and that led me down a few paths. The path I was taking wouldn’t naturally bump into fluid dynamics, but I started learning about the Navier-Stokes equation .. core in the study of fluid dynamics. There were people to talk to and papers to read. The equations look simple, but are usually too difficult to solve analytically or exactly numerically in most real-world cases. You learn tricks and the importance of the Reynolds Number as a guide for cheating. I started to understand why the waves were doing what they did, but that led to other questions including the gulls.
A few decades later I did some work on the flight of sports balls – particularly volleyballs as they’re one of the most interesting cases and that led to a friendship with Sarah Pavan and talks so far from my world that new sets of questions and thoughts sparkled into being. Those waves were a long-term serendipity gateway and there have been dozens more. I don’t know if a computer can help me in the wonder and initial serendipity part, but computer mediated communication, and synchronous is often the best kind, has certainly been an amplifier. So much of it is finding and bringing other wondering minds to the dance.
Steve’s right — what we called data-driven intelligence is not really intelligence. Instead, it is a somewhat simplistic rendering of the conclusions from the data. It lacks the ever-changing context and serendipity — something I experienced on that long drive to Siena.
July 7, 2021, San Francisco
The Oracle of Omaha, Warren Buffett, known for occasionally partaking in ice cream from Dairy Queen, is going in for a Snowflake scoop. Snowflake is a red hot data warehousing company viewed as one of the best next-generation enterprise companies to tap the public markets in 2020. In an amended S-1 filing, Salesforce Ventures and Berkshire Hathaway are … Continue reading A Buffett of Snowflake
Big data intentionally creates a concentration of data and has a corrupting influence. It really concentrates the power in the hands of whoever holds that data — governments, companies. The PC revolution of the late 1970s and 1980s and the later early Internet (of the 1990s) seemed to hold so much promise and empowered the individual. Now with big data there is a shift of power in the other direction as it concentrates power in fewer hands.Phil Zimmermann, creator of PGP