Ethical challenges of using artificial intelligence in news and television program production
Main Article Content
Abstract
Machine learning is now used in every part of news and TV shows. Most of the time, when people discuss if automation is good or bad, they are not talking about a specific task. This piece discusses the moral issues that arise when AI is used to create TV shows and news. This is why it examines how AI is used to create shows, if viewers can still understand their purpose, and if editors can still be held responsible. The way AI is used in production and communication is what creates ethical risk, not the technology itself. Thoughts on gatekeeping, media duty, and sociotechnical systems support this claim. An online poll experiment with 463 people watched short news stories and TV shows that were different based on how AI was used in the production process. This was done to test the claim. These jobs included material made by humans, speakers made by AI, visual rebuilding made by AI, the amount of human editing control, and the reveal condition. People who took part said how much they believed in the situation, how likely they were to be manipulated, how willing they were to watch and share, and how responsible they thought the situation was. The most trusted content was that which was made by humans with little or no help from AI. When AI's part became clearer, especially in AI presenters and AI-made visual reconstructions, people lost a lot of faith in the content. People didn't always trust each other more when they told the truth. Trust and responsibility went up the most when disclosure was paired with named human editing control, not when disclosure was shown on its own. These results back up a model of AI ethics in news that is based on how things are done. The level of risk relies on where AI is used in production and whether the employee is clearly responsible for their actions. AI isn't needed at all. Numerous people have talked about what this means for running newsrooms, creating rules for AI exposure, and teaching journalism.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
You are free to: Share — copy and redistribute the material in any medium or format. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
How to Cite
