Network Schools – Wayne Gerseny to https://www.nytimes.com/interactive/2022/04/03/magazine/thomas-piketty-interview u w B l.html?h I’ll smid=url-share the Is for

This morning I read two articles on the effects of technology that lead me to believe that education writers and NYTimes essayists live in parallel universes and that neither seems to see the transformative potential of technology in schooling or the relationship between technology and schooling.

in his column today titled “Our Machine Masters” David Brooks describes the eerie accuracy the artificial intelligence that creates the ability for Pandora’s ability to divine his taste in music. He then describes and laments the relationship between advances in artificial intelligence’s and large networks:

Advances in artificial intelligence will accelerate this centralizing trend. That’s because A.I. companies will be able to reap the rewards of network effects. The bigger their network and the more data they collect, the more effective and attractive they become.

As (Wired technology writer Kevin) Kelly puts it, “Once a company enters this virtuous cycle, it tends to grow so big, so fast, that it overwhelms any upstart competitors. As a result, our A.I. future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences.”

To put it more menacingly, engineers at a few gigantic companies will have vast-though-hidden power to shape how data are collected and framed, to harvest huge amounts of information, to build the frameworks through which the rest of us make decisions and to steer our choices. If you think this power will be used for entirely benign ends, then you have not read enough history.

David Brooks sees that data collection and algorithms are beneficial to the end user who is looking for entertainment and information that matches their interests. He also sees its poet to transform the way we get and process information (e.g. learn). And…. he also see that if this transformative power is not harnessed properly, can lead to malevolent consequences. 

Larry Cuban, an education historian/blogger, wrote a post yesterday describing technology and school reform as “Kissing Cousins”. Cuban contends that today’s notion of using technology to improve education is no different than the earlier ideas to improve schooling:

(Reformers) saw (and, sadly enough, still see) innovative high-tech devices as singular, even exceptional, ways of transforming teaching and learning completely divorced from previous efforts at improving classroom practice through curricular (e.g., math, social studies, science), instructional (e.g., project-based learning, direct instruction) and organizational (e.g., site-based management, charters, mayoral control) reforms.

Cuban sees this as a conceptual error.

Why? Because, school and classroom reforms including technological ones, are part of the same genetic code.

Creating “blended learning” schools, introducing online learning, or deploying tablets to each and every student is an organizational and instructional reform. Teachers using Class Dojo, Chemix School and Lab, Algebrator, and other software programs are implementing classroom organizational and curricular reforms and shaping instruction.

Technological innovations, then, are kissing cousins to curricular, instructional, and organizational reforms.

I am one of those who Cuban refers to as a utopian dreamer who believes that “…new machine technologies (e.g., film, radio, instructional television, desktop computer) (could) alter how teachers teach and students learn.” But unlike earlier utopian technology dreamers (or perhaps some of today’s utopian technology dreamers) I do not believe that the machines (e.g. film, radio, instructional television, desktop computer) are a means of reforming schools. The use of machines is based on and reinforces the paradigm of the factory school, as are technology-related concepts like “blended learning, online learning or the issuance of tablets.”

I believe reform, or more accurately transformation of schooling, could occur because of the software and algorithms Brooks describes in his column. The software and algorithms available on today’s machines, if harnessed properly, introduce the possibility of moving away from the factory model of schooling by offering each student a Pandora-like learning experience. For example, an on-line learning sequence could be tailored to match the student’s cognitive readiness to learn and could offer the instruction in a way the student “likes”. This might have seemed far fetched even a decade ago. But given the explosion of YouTube lessons and what Kevin Kelly describes as “cheap parallel computation technologies, big data collection and better algorithms” it is possible today… and if schools could replace age-based cohorts with this kind of tailored learning, the mission and purpose of schooling would change. Returning to Brooks’ essay, I could foresee that software and algorithms, if harnessed properly, could enable each student to gain a self-awareness of their thinking and behavior that would result in the positive results David Brooks foresees in his “deeply humanistic” and optimistic future.

In the deeply humanistic (vision), machines liberate us from mental drudgery so we can focus on higher and happier things. In this future, differences in innate I.Q. are less important. Everybody has Google on their phones so having a great memory or the ability to calculate with big numbers doesn’t help as much.

In this future, there is increasing emphasis on personal and moral faculties: being likable, industrious, trustworthy and affectionate. People are evaluated more on these traits, which supplement machine thinking, and not the rote ones that duplicate it.

If Brooks’ utopian vision of the future of technology is realized, schooling would focus more on personal and moral development and less on content that is available on Google or YouTube— or via stand-and-deliver instruction. And  if  his dystopian vision occurs?

In the cold, utilitarian future, on the other hand, people become less idiosyncratic. If the choice architecture behind many decisions is based on big data from vast crowds, everybody follows the prompts and chooses to be like each other. The machine prompts us to consume what is popular, the things that are easy and mentally undemanding.

Some closing questions:

• Which future is standardized testing leading us toward?
• What kind of consumers do our corporations want, “humanistic” or “utilitarian”?
• Which direction are we headed if we think of technology as machines?

And last but not least: Who will determine how these algorithms and software products will be managed?