CURMUDGUCATION: A Robot Wrote An Article. I'm Not Concerned Yet.

CURMUDGUCATION: A Robot Wrote An Article. I'm Not Concerned Yet.

A Robot Wrote An Article. I'm Not Concerned Yet.

The tech world continues its attempts to build a computer that can do language. It's not easy, as witnessed by the fact that they still haven't succeeded. But then, we don't really know how the human brain does language, either.

The current leading construct for computer-generated English is GPT-3. It can do 175 billion parameters (its predecessor had 1.5 billion). It uses deep learning. It is the product of OpenAI, a for-profit outfit in San Francisco co-founded by Elon Musk. It "premiered" in May of this year and really hit the world in July. It is a third generation "language prediction model,: and you want to remember that phrase. And you can watch this video for a "layperson's explanation,"

People have been impressed. Here's a couple of paragraphs from a gushing Farhad Manjoo  review in the New York Times

I’ve never really worried that a computer might take my job because it’s never seemed remotely possible. Not infrequently, my phone thinks I meant to write the word “ducking.” A computer writing a newspaper column? That’ll be the day.

Well, writer friends, the day is nigh. This month, OpenAI, an artificial-intelligence research lab CONTINUE READING: CURMUDGUCATION: A Robot Wrote An Article. I'm Not Concerned Yet.

Code Acts in Education: The Social Life of Artificial Intelligence in Education | National Education Policy Center

Code Acts in Education: The Social Life of Artificial Intelligence in Education | National Education Policy Center

Code Acts in Education: The Social Life of Artificial Intelligence in Education

Artificial Intelligence (AI) has become the subject of both hype and horror in education. During the 2020 Covid-19 pandemic, AI in education (AIed) attracted serious investor interest, market speculation, and enthusiastic technofuturist predictions. At the same time,  algorithms and statistical models were implicated in several major controversies over predictive grading based on historical performance data, raising serious questions about privileging data-driven assessment over teacher judgment. 

In the new special issue AI in education: Critical perspectives and alternative futures published in Learning, Media and Technology, Rebecca Eynon and I pulled together a collection of cutting edge social scientific analyses of AIed. The purpose was to add alternative analytical perspectives to studies of AIed benefits, and to challenge commercial assertions that AIed will solve complex educational problems while accruing profitable advantage for companies and investors.  

Like AI in general, AIed is social and political. It has its own long history and a complex present ‘social life’, and it is being developed in the pursuit of future visions of education. AIed has emerged in its current form from decades of prior research and development, from technological innovation, from funding practices, and from policy preoccupations with using educational data for various forms of performance measurement and prediction. Far from being merely a future vision, AIed is already actively intervening in education systems — in schools, universities, policy spaces and home learning settings — with effects that are only now coming into view. 

Yet the growth in critical studies of AI in other sectors (such as labour automation, healthcare CONTINUE READING: Code Acts in Education: The Social Life of Artificial Intelligence in Education | National Education Policy Center