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In an AI world we need to teach students how to work with robot writers


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Lucinda McKnight, Deakin University

Robots are writing more of what we read on the internet. And artificial intelligence (AI) writing tools are becoming freely available for anyone, including students, to use.

In a period of rapid change, there are enormous ethical implications for post-human authorship — in which humans and machines collaborate. The study of AI ethics needs to be central to education as we increasingly use machine-generated content to communicate with others.

Robots can write, too

AI robot writers, such as GPT-3 (Generative Pre-trained Transformer) take seconds to create text that seems like it was written by humans. In September, 2020 GPT-3 wrote an entire essay in The Guardian to convince people not to fear artificial intelligence.

AI does this through what’s called natural language processing and generation. This involves converting human language to computer commands and vice versa. To do this, machine algorithms study millions of text samples, words, sentences and paragraphs humans use to gain a general understanding of the context of human language. Then machines use that knowledge to put together text.

As recently as 2019, this kind of technology seemed a long way off. But today, it is readily available.

For example, the free Zyro content generator provides text for websites. I can select the categories “Health and Living” and “Personal Trainer” (I happen to be one, as well as an academic). In two seconds, the following text appears:

I am experienced with personal training, athletic performance, and nutrition. This includes working with children, pregnant women, older adults, people with disabilities, athletes, and anyone looking to achieve a competitive edge, improve their overall health, and overall performance. I also have an interest in alternative health, including wellness coaching and nutrition counselling. In my spare time, I enjoy spending time with my family, the outdoors, and writing.

This sums me up (despite the program knowing nothing about me) and would be fine for my website, if I had one. I have the option to generate more responses, and in two seconds, the program offers:

I am experienced in working with adults and children to improve their overall physical and emotional well-being. I have a strong desire to help you reach your goal […] I love helping others achieve their goals. I love working with others to achieve their goals. I am a mother of two healthy children and a wife to two incredible people.

While this is repetitive and Zyro does not notice the apparent error in the last sentence, these issues would be easy to correct. Text, even for niche purposes, can now be generated in a few clicks.

There are other digital tools such as paraphrasers and rewriters that can generate up to 1,000 articles from a single seed article, each of them substantially unique. Quillbot and WordAI, for instance, can rapidly rewrite text and make it difficult to detect plagiarism. WordAI boasts “unlimited human quality content at your fingertips”.

Questions for schools and universities

So what does this mean for education, writing, and society?

Of course, there’s the issue of cheating on essays and other assignments. School and university leaders need to have difficult conversations about what constitutes “authorship” and “editorship” in the post-human age. We are all (already) writing with machines, even just via spelling and grammar checkers.

Tools such as Turnitin — originally developed for detecting plagiarism — are already using more sophisticated means of determining who wrote a text by recognising a human author’s unique “fingerprint”. Part of this involves electronically checking a submitted piece of work against a student’s previous work.

Many student writers are already using AI writing tools. Perhaps, rather than banning or seeking to expose machine collaboration, it should be welcomed as “co-creativity”. Learning to write with machines is an important aspect of the workplace “writing” students will be doing in the future.




Read more:
OK computer: to prevent students cheating with AI text-generators, we should bring them into the classroom


AI writers work lightning fast. They can write in multiple languages and can provide images, create metadata, headlines, landing pages, Instagram ads, content ideas, expansions of bullet points and search-engine optimised text, all in seconds. Students need to exploit these machine capabilities, as writers for digital platforms and audiences.

Perhaps assessment should focus more on students’ capacities to use these tools skilfully instead of, or at least in addition to, pursuing “pure” human writing.

But is it fair?

Yet the question of fairness remains. Students who can access better AI writers (more “natural”, with more features) will be able to produce and edit better text.

Better AI writers are more expensive and are available on monthly plans or high one-off payments wealthy families can afford. This will exacerbate inequality in schooling, unless schools themselves provide excellent AI writers to all.

We will need protocols for who gets credit for a piece of writing. We will need to know who gets cited. We need to know who is legally liable for content and potential harm it may create. We need transparent systems for identifying, verifying and quantifying human content.




Read more:
When does getting help on an assignment turn into cheating?


And most importantly of all, we need to ask whether the use of AI writing tools is fair to all students.

For those who are new to the notion of AI writing, it is worthwhile playing and experimenting with the free tools available online, to better understand what “creation” means in our robot future.The Conversation

Lucinda McKnight, Senior Lecturer in Pedagogy and Curriculum, Deakin University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Robot Authors


The link below is to an article that takes a look at the rise of the robot author.

For more visit:
https://www.theguardian.com/books/2019/mar/25/the-rise-of-robot-authors-is-the-writing-on-the-wall-for-human-novelists

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We, robot: the computer co-authoring a story with a human writer



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Leah Henrickson, Loughborough University

In Isaac Asimov’s I, Robot, a collection of nine short stories about robotics, Asimov explores the possibilities of human-computer interaction. How can humans and computers co-exist? How can they work together to make a better world?

A research group from the Meertens Instituut in Amsterdam and the Antwerp Centre for Digital Humanities and Literary Criticism recently introduced a new digital creative writing system. Using a graphical interface, an author drafts a text sentence by sentence. Then, the system proposes its own sentences to continue the story. The human and the computer work together to create what the system’s developers call “synthetic literature”.

The paper detailing this project describes the text generation system as an attempt to:

Create a stimulating environment that fosters co-creation: ideally, the machine should output valuable suggestions, to which the author retains a significant stake within the creative process.

How to train your robot

To learn language and sentence structure, the system has been trained using the texts of 10,000 Dutch-language e-books. Additionally, the system was trained to mimic the literary styles of such renowned authors as Asimov and Dutch science fiction author Ronald Giphart by generating sentences that use similar words, phrases, and sentence structures as these authors.

As part of this year’s annual Nederland Leest (The Netherlands Reads) festival, Giphart has been trialling the co-creative writing system to write a tenth I, Robot story. Once Giphart’s story is completed it will be published at the end of a new Dutch edition of Asimov’s classic text. Throughout November, participating libraries throughout the Netherlands will be offering free copies of this edition to visitors to get people thinking about this year’s festival theme: Nederland Leest de Toekomst (The Netherlands Reads the Future).

As Giphart types new sentences into the system’s graphical interface, the system responds by generating a selection of sentences that could be used to continue the story. Giphart can select any of these sentences, or ignore the system’s recommendations altogether.

The point of the system, its developers explain, is to “provoke the human writer in the process of writing”. Giphart says he still considers himself “the boss, but [the system] does the work”. One article even described the system as being ideal “for those who have literary aspirations, but who lack talent”.

Can a computer be creative?

The “synthetic literature” referred to by this system’s developers implies a combined production effort of both human and computer. Of course, the human still guides production. As co-developer Folgert Karsdorp explained: “You have numerous buttons to make your own mix. If you want to mix Giphart and Asimov, you can do that too.” The system follows its user’s direction, responding by using its own capacity for creativity.

But can a computer ever be truly creative? This is a question that the field of computational creativity has been studying since computers were invented. The field generally accepts that a computer can be called creative if its output would be considered creative had it been produced by a human.

Computational creativity debates are all rooted in one underlying question: is the computer merely a tool for human creativity, or could it be considered a creative agent itself? In a discussion about computer-generated art, creativity scholar Margaret Boden noted that:

It is the computer artist [the developer] who decides what input a system will respond to, how the system will respond, how unpredictable the system’s output will be, and how transparent the system’s functionality will be to users.

Even the most unpredictable output, according to Boden, results from choices the computer artist has made. While a developer may not be able to predict a system’s exact output, the output nevertheless reflects the choices the developer has made while programming.

Computer systems can be trained to mimic the language and sentence structure of particular writers.
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The co-creative writing system Giphart is using isn’t able to produce an entire book by itself, but it can produce paragraphs that continue Giphart’s story for him. Giphart, though, ultimately has the power to choose what computer output he uses.

But does this mean that Giphart alone will be credited as the author of his Ik, robot story, or will his computer be given credit as a co-author? It’s still unclear. Although it could be hotly debated whether the creative writing system is just a tool for Giphart’s vision or could be considered an agent itself, we won’t be seeing the demise of human authors any time soon.

One Nederland Leest blog post compares this new method of writing to the evolution of the electric guitar. It may have existed for nearly a century, but it wasn’t until Jimi Hendrix showed us how to really play the instrument that its potential was realised. Similarly, we still need to discover how to “play” this writing system to get the best results, whatever they might be.

So is synthetic literature the future? Maybe. Keep reading to find out.

The ConversationA video explaining the project is available here, in Dutch.

Leah Henrickson, PhD Candidate, Loughborough University

This article was originally published on The Conversation. Read the original article.