The Power of Generative Artificial Intelligence: Using AI to Brainstorm about Critique, Privacy and Predictive Policing
Journalists have been trying out generative artificial intelligence tools to see whether they can help them do their jobs better. Artificial intelligence can only call sources, and can not tell you everything, but it can still produce half-decent transcripts of those calls and give you a summary.
We may use machines to come up with story ideas. An AI might help the process of brainstorming with a prompt like “Suggest stories about the impact of genetic testing on privacy,” or “Provide a list of cities where predictive policing has been controversial.” This may save some time and we will keep exploring how this can be useful. But some limited testing we’ve done has shown that it can also produce false leads or boring ideas. In any case, the real work, which only humans can do, is in evaluating which ones are worth pursuing. We can acknowledge the sources that the tool used to generate information comes from.
We want to be on the forefront of new technology and ethical, but also be circumspect. There are some ground rules for how we are using the current set of generative tools. We recognize that AI will develop and so may modify our perspective over time, and we’ll acknowledge any changes in this post. We welcome feedback in the comments.
The current artificial intelligence tools are prone to both errors and bias and can often produce dull, unoriginal writing. Someone who writes for a living needs to constantly be thinking about the best ways to express complex ideas in their own words. Finally, an AI tool may inadvertently plagiarize someone else’s words. If a writer uses it to create text for publication without a disclosure, we’ll treat that as tantamount to plagiarism.
We may try using AI to suggest headlines or text for short social media posts. An editor has to approve the final choices for accuracy due to the fact we generate lots of suggestions manually. Using an AI tool to speed up idea generation won’t change this process substantively.
The Writers Guild of America: Changing the Media Landscape in the Rise of the Stream Era and the Implications for Television and Film Production
A strike by the Writers Guild of America would cause massive disruption to television and film projects all over the industry, as the guild began negotiations with the studios on Monday over a contract that is set to expire on May 1.
The guild is heading to the Sherman Oaks bargaining table seeking higher compensation for writers, a boost in contributions to pension and health funds, and better workplace standards.
Most notably, the guild wants to factor in the streaming economy into compensation packages for its members. Residual fees have aided the writers of shows and movies for a long time. But those fees are vanishing in the streaming era, which is where a great deal of projects ultimately land these days.
The newsletter contained a version of the article. The evolving media landscape is chronicled in the daily digest.
There are often less episodes in a show with the rise of streaming. Shows that run on broadcast networks typically include more than 20 episodes in a season. That’s not the case with shows that are ordered by Netflix and others.
Source: https://www.cnn.com/2023/03/20/media/wga-hollywood-reliable-sources/index.html
The Alliance of Motion Picture and Television Producers (AMPTP) is negotiating a new standards for artificial intelligence (A.I.G.)
It is a good idea to be a taxi driver, if you can see a bunch ofUbers on the road. “Being a working writer is much harder than it used to be. The level of compensation, the treatment and expectations are all fundamentally different than they were.”
The guild is asking for standards around the use of artificial intelligence in order to keep up with the revolution. It wants the use of A.I. regulated, in terms of material created for the studios.
It is not clear what the powers of Hollywood will agree to, and there are many hurdles the guild has to overcome to deliver its objectives to members.
The guild told members that the talks will last for two weeks. There is a break during which it will update its members on progress. Negotiations would resume with the goal of an agreement by May 1. The guild did not respond to a request seeking further comment on Monday.
The Alliance of Motion Picture and Television Producers said it’s approaching the negotiations with the long-term health and stability of the industry in mind.
“We are all partners in charting the future of our business together and fully committed to reaching a mutually beneficial deal with each of our bargaining partners,” the AMPTP said in a statement. “The goal is to keep production active so that all of us can continue working and continue to deliver to consumers the best entertainment product available in the world.”
The WGA Proposal: Bringing Artificial Intelligence to the Foreground and Making It Into a Proto-Script
The difference between literary material and source material is that source material is pre-existing work that can be adapted for a different project, while literary material is the creation of a writer on their own. By ruling out any content generated by an AI tool like ChatGPT as being literary material or source material, the proposal would effectively make it possible for writers to “draft” stories using ChatGPT prompts, fashion those stories into scripts, and then claim sole writing credits for the entire endeavor. Were a studio to get into the business of cranking out AI-generated proto-scripts and then passing those to human creators to punch up, those people could still be considered the project’s original writers. The proposal did not account for the fact that a fully artificial intelligence script could be written.
Of course, a proposal is just a proposal, the AMPTP hasn’t committed to anything just yet, and it’s always important to consider where these sorts of leaks might be coming from.
But it feels notable that the WGA’s floating the idea of normalizing AI-sourced content given rising concerns (in some creative circles especially) about the datasets tools like these like are trained on. It wouldn’t be hard to think of disputes about plagiarism and original authorship stemming from the fact that this kind of technology creates things based on other things already seen before. The human creative process can be said of, and it’s last point can also be said of. It feels more than fair to say that the WGA’s wading into new territory that isn’t quite as old seems very difficult to navigate.