How will ChatGPT, DALL-E and other AI tools impact the future of work? We asked 5 experts

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From steam power and electricity to computers and the internet, technological advancements have always disrupted labor markets, pushing out some careers while creating others. Artificial intelligence remains something of a misnomer — the smartest computer systems still don’t actually know anything — but the technology has reached an inflection point where it’s poised to affect new classes of jobs: artists and knowledge workers.

Specifically, the emergence of large language models – AI systems that are trained on vast amounts of text – means computers can now produce human-sounding written language and convert descriptive phrases into realistic images. The Conversation asked five artificial intelligence researchers to discuss how large language models are likely to affect artists and knowledge workers. And, as our experts noted, the technology is far from perfect, which raises a host of issues — from misinformation to plagiarism — that affect human workers.

To jump ahead to each response, here’s a list of each:

Creativity for all – but loss of skills?

Potential inaccuracies, biases and plagiarism

With humans surpassed, niche and ‘handmade’ jobs will remain

Old jobs will go, new jobs will emerge

Leaps in technology lead to new skills

Creativity for all – but loss of skills?

Lynne Parker, Associate Vice Chancellor, University of Tennessee

Large language models are making creativity and knowledge work accessible to all. Everyone with an internet connection can now use tools like ChatGPT or DALL-E 2 to express themselves and make sense of huge stores of information by, for example, producing text summaries.

Especially notable is the depth of humanlike expertise large language models display. In just minutes, novices can create illustrations for their business presentations, generate marketing pitches, get ideas to overcome writer’s block, or generate new computer code to perform specified functions, all at a level of quality typically attributed to human experts.

These new AI tools can’t read minds, of course. A new, yet simpler, kind of human creativity is needed in the form of text prompts to get the results the human user is seeking. Through iterative prompting — an example of human-AI collaboration — the AI system generates successive rounds of outputs until the human writing the prompts is satisfied with the results. For example, the (human) winner of the recent Colorado State Fair competition in the digital artist category, who used an AI-powered tool, demonstrated creativity, but not of the sort that requires brushes and an eye for color and texture.

While there are significant benefits to opening the world of creativity and knowledge work to everyone, these new AI tools also have downsides. First, they could accelerate the loss of important human skills that will remain important in the coming years, especially writing skills. Educational institutes need to craft and enforce policies on allowable uses of large language models to ensure fair play and desirable learning outcomes.