Tech Progress Is Slowing Down

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https://news.ycombinator.com/newsfaq.html>

They point to patent research, showing that innovation in areas outside of computers and electronics has slowed down. Then admits "of course" computers and electronics aren't included in this. But computers and electronics dominate our world. If you exclude them and say "tech progress is slowing down!", you're saying almost nothing at all, because you've excluded the thing that accounts for our currently-alleged rapid rate of technological progress.

He does attempt to cover this point by asserting that increases in processor performance are slowing down. This is enough for him to draw the conclusion of: "for computers [...] the period of rapid exponential growth will soon become history." This is a massive logical leap. Processor performance isn't the only component of technological progress in the wide field of computers and electronics, and that's especially obvious in the current time where rapid progress is occurring in ML algorithms.

I think this subject is a worthy point of inquiry, but it seems to me that the article is simply taking facts and drawing unwarranted conclusions from them.

This is inevitable in a society where progress is predicated on return on investment.

John Stuart Mill distinguishes science from the "arts" (the term for "technology" in the 19th century) as "science most conveniently follows the classification of causes, while arts must necessarily be classified according to the classification of the effects", from Essays on some unsettled Questions of Political Economy.[1]

There's some discussion of the nature of technology, W. Brian Arthur, The Nature of Technology , and Kevin Kelley's What Technology Wants, as well as several titles by Steven Johnson. The contribution of philosophy to the question is generally unsatisfying, though there are Jaques Ellul, Lewis Mumford, Michel Foucault, and Martin Heidegger.[2] None of these are themselves technologists, which whilst providing some stand-off distance also manifests much ignorance.

I've found useful to consider what the specific mechanisms of technology are, and have come up with a nine-part breakdown, which I refer to as the ontology of technological mechanisms:

- Fuels & energy sources: Primary means for effecting change in a system. Biomass, fossil fuels, nuclear energy, environmental fluxes (solar, wind, hydro, geothermal, etc.)

- Materials: Stuff we build and process with, both structural and feedstocks. Stone, wood, fibre, vitrified materials, metals, chemicals, fluids, etc.

- Power transmission and transformation: Conversions between types or forms of power, from simple mechanisms to electronics and quantum effects.

- Process knowledge: Specific "how to" knowledge, "technology" in the vernacular.

- Causal knowledge: Understanding of properties and mechanisms, "science" in the vernacular.

- Networks: Links and nodes, physical or virtual. Transportation, communications, knowledge itself.

- Systems: Process with feedback.

- Information: Sensing, parsing, storage & retrieval, processing, and transmission.

- Hygiene effects: Dealing with unintended or undesired consequences.

The classification has seemed reasonably stable and useful to me for some years now.

From this a few aspects become clearer:

1. Each modality has its capabilities and limitations. E.g., materials vary in properties and abundance.

2. Some modalities scale linearly (e.g., the effects of additional energy are generally directly proportional to inputs), some exponentially (networks and systems), others seem to be emergent and impose non-evident but long-term costs (hygiene).

3. Virtually all exponential change seems to involve or rely highly upon network effects. These are only a limited set of modalities.

4. Tremendous advances in raw capabilities in specific areas (e.g., information) seem to provide at best limited real-world outcomes. E.g., multi-millionfold increases in computational capabilities have resulted in extension of useful weather forecasting only by a factor of days. Efficiencies of automobile and aircraft transport improve with increased informational capacities, but only to inherent limitations defined by physics (drag coefficients, Carnot / Rankine efficiency).

We can also look at specific areas of technological progress ... or stagnation ... and see where these fall within the structure. Keep in mind that a given real-world technology, say, computer chips, typically covers a set of these factors, say, networks, systems, materials, and process knowledge, in the case of semiconductors.

What all of this suggests to me is that even with considerable future potential in certain areas, we're likely to see limitations imposed by other elements of the ontology.

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Notes:

1. Previously discussed with a longer quotation here: https://news.ycombinator.com/item?id=23000911>. Source: http://www.gutenberg.org/files/12004/12004-h/12004-h.htm#FNa...>

2. See generally: https://plato.stanford.edu/entries/technology/>