Can you imagine reading a news report written by a robot? Would you read a novel written by artificial intelligence? It might just be possible by the way artificial intelligence is advancing.

Let’s take Grammarly as an example. It can already form better or equally-proper sentences like humans. This AI predictive text technology is already used in phones and email applications and much of everyday writing that humans do might soon be done by AI.

According to Gartner, by 2022, AI and similar technology will automate the production of 30% of all content found on the internet. Astonishingly, some texts like opinion articles and scripts are already being written by AI. MSN, a news website dismissed 50 freelance news editors and replaced them with AI-driven bots. Freelance sports writers at 30 Swedish news sites were replaced by automated sports news robot systems. Based on this, literacy, in today’s world, means interacting with rapidly advancing AI. In schools, today’s children should no longer be taught just writing. Instead, writing should include skills that go beyond the capabilities of artificial intelligence.

In 2019, a New Yorker magazine experimented to see if Open AI’s (an IT company) natural language generator GPT-2 could write an article in the New Yorker magazine’s unique style. But this experiment had limited success because the AI generator made many errors. In 2020, GPT-3’s new version which was trained with more data wrote an article for The Guardian newspaper. The headline said “A robot wrote this entire article. Are you scared yet, human?”

This article was much improved from the previous one and leaves a question mark on the future of journalism.

Do Robots Have A Soul For Writing?

The day is far when robots will mimic human nature to its maximum of 100%. School curriculum needs to make developments based on what AI cannot do, especially when it comes to creativity. It has been observed that AI writing has a voice but no soul. According to New Yorker’s John Seabrook, human writers give, “color, personality, and emotion to writing by bending the rules.” Students, therefore, should be encouraged to break the rules of writing, something that an AI cannot do as machines are trained on a finite amount of data to predict and replicate, not to improvise.

The Right Writing

AI is not yet as complex as the human mind. Humans can write humor and satire. We know words can have multiple emotions attached to them. A reader can make a judgment between good and bad writing, a writing that has empathy, perception, and insight. Humans possess sophistication versus an AI machine.

According to the Institute For The Future, social intelligence is an essential skill for the future generation. Social intelligence is the ability to connect to others in a deep and direct way. It requires adaptive thinking, cross-culture compatibility, and virtual collaboration. These skills are in stark contrast to what an AI bot can do, at least, as of now. Creativity should be fostered with machines and not only by machines. While we can’t turn away from the reality that artificial intelligence is here to stay, kids should be taught skills that are greater than just writing to coexist in a workforce with AI robots.

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By learning to deviate from known information in the same way that humans do, an “imagination” algorithm for artificial intelligence (AI) is able to identify previously unseen objects from written descriptions.

The algorithm, developed by KAUST researcher Mohamed Elhoseiny in collaboration with Mohamed Elfeki from the University of Central Florida, paves the way for artificial imagination and the automated classification of new plant and animal species.

“Imagination is one of the key properties of human intelligence that enables us not only to generate creative products like art and music, but also to understand the visual world,” explains Elhoseiny.

Artificial intelligence relies on training data to develop its ability to recognize objects and respond to its environment. Humans also develop this ability through accumulated experience, but humans can do something that AI cannot. They can intuitively deduce a likely classification for a previously unencountered object by imagining what something must look like from a written description or by inference from something similar. In AI, this ability to imagine the unknown is becoming increasingly important as the technology is rolled out into complex real-world applications where misclassification or misrecognition of new objects can prove disastrous.

Also important is the sheer volume of data needed to reliably train AI for the real world. It is unfeasible to train AI with images of even a fraction of the known species of plants and animals in the world in all their permutations, let alone the countless undiscovered or unclassified species.

Elhoseiny and Elfeki’s research aimed at developing what is called a zero-shot learning (ZSL) algorithm to help with the recognition of previously unseen categories based on class-level descriptions with no training examples.

“We modeled the visual learning process for ‘unseen’ categories by relating ZSL to human creativity, observing that ZSL is about recognizing the unseen while creativity is about creating a ‘likable unseen,'” says Elhoseiny.

In creativity, something novel but pleasing or “likable” must be different from previous art, but not so different as to be unrecognizable. In the same way, Elhoseiny and Elfeki carefully modeled a learning signal that inductively encourages deviation from seen classes, yet not pushed so far that the imagined class becomes unrealistic and loses knowledge transfer from seen classes. The resultant algorithm showed a consistent improvement over the state-of-the-art benchmarks for ZSL.

“One of the possible applications of our approach is in identifying unknown species,” says Elhoseiny. “AI that is powered with this technology could help report species sightings without pictures, just with language descriptions.”

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