Considering the recent proliferation of artificial intelligence (AI) in our everyday lives, many believe it will profoundly impact education in the upcoming times, and Harvard professor Bharat N. Anand has revealed in what way this might happen.
As it happens, Professor Anand, who is the vice provost for Advances in Learning at Harvard, pointed out the speed at which new technologies have been gaining traction in modern history, as he spoke at a recent technology event, according to a video streamed on March 10.
Indeed, he noted that it took 20 years for computers to reach about 30% penetration in the US economy, radio took about 20 years to reach half the population, TV took about 12 years, smartphones about seven years, smart speakers about four years, and chatbots about two and a half years.
Generative AI in education: Access
Anand challenged some theories related to generative AI and education, including that the transformative potential of AI stems from how smart its output is, that educators should wait until hallucinations decline, that bot tutors are unlikely to be superior to active learning, that AI will ultimately level the education playing field, and that the best thing we can do is provide access to everyone and let them experiment.
In the words of this Harvard professor, generative AI’s transformative potential comes from how it changes the input to software rather than its output, and that its fundamental impact is on how this intelligence is accessed.
“We’ve been actually experiencing AI for 70 years, machine learning for upwards of 50 years, deep learning for 30 years, transformers for seven to eight years. This has been an improvement gradually over time. There were some discreet changes recently, but the fundamental reason why this has taken off has less to do with the discrete improvements in intelligence two years ago as opposed to the improvement in access or the interface that we have with intelligence.”
Furthermore, he stressed that the evolution of human-computer communication has gone exactly in the opposite direction from human-human communication, which started out with talking to each other around campfires, proceeded with pictures on the walls (graphics), then onto writing scrolls and books (formal text), and culminated with ones and zeroes (mathematics).
In terms of human-computer communication, it started with punch cards or ones and zeroes 60-70 years ago, moving to DOS prompts or commands that we had to input. Then the big step happened with the transition from Windows 1.0 to Windows 3.0, or to a graphical user interface, “and suddenly seven-year-old kids could be using computers.”
Shrinking distance between humans and computers
Anand argues that this is more similar to the revolution we’re witnessing at the moment, which is AI moving from the province of computer programmers, software engineers, and tech experts, to being “available to every one of us on the planet through a simple search bar” following the launch of ChatGPT.
“Where is this going? Probably towards just audio, (…) neural, reading emotions, you might argue basically us grunting and shaking our arms. You could argue we are regressing as a species. On the other hand, you could argue that in fact what’s happening is that the distance between humans and computers is fundamentally shrinking. Fundamentally, this is about access.”
As an example, he mentioned Photoshop, which a lot of people spend years trying to master, but we no longer need this kind of expertise because we can get it by communicating directly with computers in natural language.
Organizational restructuring with generative AI
On top of that, he envisions some form of consolidation taking place within bottom functions in organizational structure, which consists of experts in different kinds of software, some in Photoshop, some in Concur, some in Epic, and the like.
“The middle managers who used to oversee all these software experts, it’s likely we’re going to see shrinkage there. In fact, you could argue all the way that the person at the top could in fact do sales, graphics design, design, marketing, everything by just interacting directly with the computer.”
Meanwhile, generative AI is being actively introduced in educational organizations’ syllabuses, with one prominent example being Towson University in Maryland and its AI Task Force, which have created sample text with recommended language professors to use as they see fit.
Elsewhere, Meta has announced the availability of a new Meta for Education to the general public, giving students access to mixed and virtual reality through Meta Horizon managed service, with the goal of providing them with an immersive teaching and learning experience.
Featured image via TEDx Talks YouTube
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