Generative AI is a type of artificial intelligence that can generate content, like images, videos, or text. Chances are you might be familiar with text-based examples such as ChatGPT and photo examples such as DALL-E, Sora, or Stable Diffusion. Generative AI models are trained on large datasets and can create new content by learning patterns and structures from the data they are trained on. As you may already realize, AI-generated content is often difficult to discern without sophisticated analysis.
While generative AI has many potential positive applications, such as generating fun art, creating virtual worlds, helping write articles and assisting in creative design, there are also negative impacts.
Some of these negative impacts include:
- Misinformation and Fake Content
Generative AI can be used to create realistic but fake photos and videos that can be used to spread misinformation or deceive people. Deepfakes, which are generated using AI, can manipulate images or videos to make it appear as if someone said or did something they did not, leading to potential harm or damage to a person’s reputation. Unfortunately, the threat does not only apply to individuals. To get a sense of the potential harm to businesses, imagine fraud caused by an insurance claim utilizing fake photos. - Privacy Concerns
Generative AI can create content that invades people’s privacy by generating images or videos that reveal personal information or depict individuals in compromising situations. This can result in loss of privacy, harassment, or even blackmail, sometimes putting the burden on the individual to prove that the content is fake. - Bias and Discrimination
Generative AI models learn from large datasets, which may contain biases present in the data. As a result, generative AI content can also carry those biases, leading to the creation of images or videos that perpetuate stereotypes, discrimination, or prejudice against certain groups of people. Without systems to audit the source and nature of the training data, it becomes nearly impossible to assume fairness. - Infringement Concerns
Generative AI raises ethical concerns related to ownership and consent. For example, using generative AI to create content without proper attribution or permission from the original creators may result in copyright infringement or intellectual property violations. Rest assured, blaming AI is unlikely to work as an excuse for plagiarism. - Emotional Impact and Confusion
Generative AI-generated content, such as deepfakes, can have psychological and emotional impacts on individuals who may be deceived by the content or have their emotions manipulated. This can result in mistrust, anxiety, and emotional distress. We live in a world where people accept photos and video content at face value. Once people are trained otherwise to always suspect the veracity of content, the deeper implication is they may also begin to raise doubts about legitimate content. - Legal and Security Issues
The use of generative AI in creating fake content can have legal and security implications. For example, it can lead to legal disputes, defamation cases, or security threats when used for malicious purposes, such as spreading misinformation, fraud, or cyber-attacks. Imagine the chaos or fraud that might ensue from malicious phone calls generated in the voice of a high-authority figure in both corporate and political contexts.
It is important to be aware of the potential negative impacts of generative AI on photos and videos and to develop appropriate safeguards, guidelines, and regulations to mitigate these risks and ensure responsible and ethical use of this technology.
While many AI creators and corporations have proposed pausing AI development to prevent the potential harms from spiraling out of control, it may be too late – the truth is malicious actors would never embrace such a truce.
Instead, the best defense is having a system that can discern what’s real from what’s fake and at a more subtle level, what is authentic and what has been generated. With that sort of system in place, it becomes much easier to focus on the positive aspects of generative AI without the threats and incidentally, also reflects our vision at Attestiv.
(this article was updated December 2024)
