While generative AI offers powerful capabilities and innovative solutions, it’s crucial to be aware of potential risks and ethical considerations associated with its use.
Truth and Accuracy
Hallucinations: Generative AI can produce inaccurate, misleading or completely false information using a confident voice.
Bias: Generative AI can produce output with subtle or blatant biases because of programming and the source training data.
Mediocre quality: Generative AI struggles with context, deeper meanings or emotional tone. Depending on its training data, the output can seem bland or uninspired. Newer AI models are often far superior to older models.
Ethics and Rights
Intellectual property: Generative AI can be trained on copyrighted material and intellectual property used without consent.
No accountability: Generative AI sources are often kept opaque. Private information you input may be shared with others without your knowledge or permission.
Lack of values: Generative AI programming often doesn’t fully consider the consequences or damages that may result from its use. Guardrails for AI systems are still in development.
Tech Issues
Not current: Some Generative AIs do not capture up-to-date news and information, so their output can be outdated.
Resource hungry: AI models are very expensive to develop and the massive power consumption to train them and respond to queries can be bad for the environment.
Security risks: AI tools developed by individuals or small operations may not have adequate safeguards to protect privacy and block malware.
Based on a model published by Visual Capitalist