Word prediction on steroids and the authorship questions it raises

I’ve been thinking lately about the future of word prediction (and phrase and sentence prediction). We’re at a point now where, without the user typing a single letter, but instead just selecting predicted words, syntactically and semantically coherent messages can emerge. This is obviously a huge boon for anyone who needs help typing and actually knows the meanings of the predicted words and what they want to say with them.

But what about those who don’t? What about all those individuals with autism who use AAC not because they have problems with motor control, but because they have problems with language? How do we know that someone isn’t simply selecting words at random that they don’t understand? Worse, given how text-prediction software can adapt to the styles and content of particular users, how do we know that the AI hasn’t been trained through earlier sessions that were mediated through on or another form of facilitated communication to output messages that originated with a facilitator—even when that person is no longer in the room?

The answer, as with the more standard, immediate cases of FC, is message-passing testing.

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The NIH falls for FC: How did this happen and is it reversible?

Some six weeks ago, the National Institutes of Deafness and Communication Disorders (NIDCD) sponsored a conference entitled “Minimally Verbal/Non-Speaking Individuals With Autism: Research Directions for Interventions to Promote Language and Communication.” The NIDCD is a member of the U.S. National Institutes of Health, and so is funded by Congress. All of us citizens and taxpayers, therefore, should be concerned by the fact that this event served—albeit only in part, and mostly indirectly—to promote facilitated communication. It did so primarily by showcasing two “non-speaking” autistic individuals who type out grammatically well-formed, syntactically sophisticated, vocabulary-rich messages on keyboards: messages that show no evidence of the language learning impairments associated with non-speaking autism.

Once the conference’s program became available, several autism experts expressed concern that an FC user was listed as a panelist, that the event featured “S2C proponent Vikram Jaswal presenting a flawed study of S2C users”, that the NIH was “giving credence to FC”, and that the only other representative of non-speaking autism was someone who had told the world, years ago, “I can talk. I can even have a conversation with you.”

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ChatGPT on who we are

Who is Catherine Johnson?

Catherine Johnson is a British playwright, screenwriter, and novelist. She was born on October 14, 1957, in London, England. Johnson is best known for her work as the writer of the book for the hit stage musical “Mamma Mia!” which features the music of Swedish pop group ABBA. The musical has been a huge commercial success, with productions all over the world, as well as a film adaptation released in 2008.

In addition to her work on “Mamma Mia!”, Johnson has written a number of other plays, including “Shang-a-Lang,” “Little Baby Nothing,” and “Rag Doll.” She has also written several books for children and young adults, including “The Dying Game,” “Sawbones,” and “The Curious Tale of the Lady Caraboo.”

Johnson has been nominated for several awards for her work in both theatre and literature, and has won several, including the Writers’ Guild Award for Best Play for “Not Quite Gospel” in 1993, and the U.K. Theatre Award for Best Musical Production for “Mamma Mia!” in 2000.

Who is Catherine Johnson, Temple Grandin’s co-author?

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The AI has summoned another zombie idea back from the dead. This time it’s the flipped classroom, a concept that never works but also never dies:

While ChatGPT and similar tools will not be replacing clinicians anytime soon, the technology does highlight the triviality of the memorization of medical facts. …

The performance of ChatGPT on the USMLE [U.S. Medical Licensing Exam] is a wake up call that the medical school curriculum and evaluations systems must change.

For years, leading medical educators like Charles Prober, MD, founding director of the Stanford Center for Health Education, have been advocating for a move away from traditional lectures and a memorization of facts. He advocated for a “flipped classroom” approach to medical education, where students can gather facts and lectures on their own time, and then come to the classroom to interact with professors and peers to practice problem-solving and data analysis. … This approach aims to de-emphasize the memorization of medical facts and focus on interacting with data and resources to develop critical thinking skills.

– Beyond Memorization: AI Can Revolutionize Medical Education — Tools like ChatGPT could catalyze the trend toward a “flipped classroom” by Justin Norden, MD, MBA, MPhil, and Henry Bair

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What authorship tests have shown us about RPM and S2C

For outside observers, possibly the biggest problem with Rapid Prompting Method (RPM) and Spelling to Communicate (S2C) is that practitioners unanimously resist validity testing. This, quite naturally, raises questions. Why is not one single practitioner or family member concerned and/or curious enough about authorship and communication rights to seek out rigorous authorship testing—even with neutral investigators they don’t consider antagonistic? Why is not one single RPMed/S2Ced typer interested in proving definitively to the general public that it’s really him/her/them typing?

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