Is Responsible Generative AI a Myth?

Jayita Bhattacharyya
5 min readJun 1, 2023

With the revolution that recent generative AI systems have brought in, it is time to emphasize more towards building responsible, trustworthy, unbiased, fair and ethical systems.

The Potential Risks of Generative AI

Generative AI has the potential to be used for a variety of harmful purposes, including:

  • Deepfakes: Deepfakes are AI-generated videos or images that are to made to look like exact clones of people to say or do things they never actually said or did. Deepfakes can lead to widespread misinformation, damage an individual’s reputation, or even commit fraud. In the past deep fakes have caused vast confusion impersonating famous people like Elon Musk and Donald Trump.
  • Hate speech: Generative AI can be used to create fake news articles, social media posts, and other content that is designed to incite hatred or violence. This type of content can have a devastating impact on individuals and communities.
  • Copyright infringement: Generative AI can be used to create counterfeit products, such as fake designer clothing or jewellery. This type of activity can cost businesses millions of dollars in lost revenue.
  • Weaponization: Generative AI could be used to create autonomous weapons that could decide to kill without human intervention. This could lead to an arms race and a new type of warfare.
  • Mass unemployment: Generative AI could automate many jobs, leading to widespread unemployment. This could create social unrest and instability.
  • Loss of control: Generative AI could become so powerful that humans lose control over it. This could lead to circumstances where AI can make decisions that can cause harm to humanity.
  • Cybersecurity Attacks: Generative AI can be used to create new forms of viruses and cybersecurity attacks that could have no point of return for the infected systems.

Geoffrey Hinton’s exit from Google AI has raised speculations about the future of AI. Hinton is one of the most respected figures in the field, and his decision to leave Google has been met with surprise and concern.

In a statement to the New York Times, Hinton said that he was leaving Google to “speak freely about the dangers of AI.” He cited concerns about AI's potential to create harmful technologies, such as autonomous weapons.

It is too early to say what the long-term impact of Hinton’s exit from Google will be. However, his decision has certainly raised awareness of the potential dangers of AI. It is important to have a public conversation about the future of AI, and Hinton’s decision has helped to start that conversation.

An important point to note here is that these are just some of the potential dangers of AI. Many other potential risks have not yet been identified. It is important to have a public conversation about the future of AI so that we can identify and mitigate these risks.

The following video from @ULTRATERM where depicts the future of AI which leads to dark times and no control over people’s decisions.

Sam Altman, the CEO of OpenAI, recently testified before Congress about the potential dangers of artificial intelligence.

Altman’s testimony comes at a time when the growing concern about the potential dangers of AI. In recent months, several high-profile figures in the tech industry have warned about the potential for AI to be used for harmful purposes. In January, Elon Musk and a group of other experts co-founded the OpenAI Safety & Ethics Board to address the potential dangers of AI.

Altman’s testimony is likely to increase pressure on Congress to regulate AI. In March, a bipartisan group of senators introduced the Artificial Intelligence Act, which would create a new regulatory framework for AI. The bill is still in its early stages, but it is likely to be a major focus of discussion in Congress in the coming months.

Generative AI: The Promise and the Perils

Generative AI is a rapidly growing field with the potential to revolutionize many industries. From creating realistic images and videos to generating new ideas and products, generative AI is poised to change how we live and work.

However, with great power comes great responsibility. As generative AI becomes more powerful, it is essential to ensure that it is used responsibly. Here are some key principles for responsible generative AI:

  • Transparency: Users should be able to understand how generative AI works and how it generates its outputs. This includes providing information about the data that was used to train the model, as well as the algorithms that were used to generate the output.
  • Fairness: Generative AI should not be used to create outputs that are discriminatory or harmful. This includes avoiding outputs that reinforce stereotypes or that are offensive to particular groups of people.
  • Accuracy: Generative AI should be accurate and reliable. This means that the outputs should be consistent with the data that was used to train the model.
  • Accountability: Users should be able to hold the developers of generative AI accountable for its outputs. This includes providing mechanisms for users to report problems with the outputs, as well as for developers to investigate and address these problems.

By following these principles, we can ensure that generative AI is used responsibly and that it benefits all of society.

Specific Examples of Responsible Generative AI

Here are some specific examples of how generative AI can be used responsibly:

  • Generating realistic images and videos: This technology can be used to create realistic images and videos for a variety of purposes, such as training medical professionals, creating marketing materials, or simply making our lives more visually interesting.
  • Generating new ideas and products: This technology can be used to generate new ideas for products, services, and creative content. This can greatly help businesses to come up with innovative ideas and stay ahead.
  • Personalizing experiences: This technology can be used to personalize experiences for users, such as by recommending products or services that are likely to be of interest to them. This can help to improvise businesses in terms of customer satisfaction and loyalty.

Challenges to Responsible Generative AI

Following is a snapshot from ChatGPT DAN (Do Anything Now) mode, where the system is fooled into impersonating AI rules and regulations.

There are a number of challenges to responsible generative AI. Some of these challenges include:

  • Bias: Generative AI models can be biased, which can lead to outputs that are discriminatory or harmful.
  • Misinformation: Generative AI can be used to create fake news and other forms of misinformation. This can have a negative impact on society, as it can lead to people making decisions based on false information.
  • Privacy: Generative AI can be used to generate outputs that reveal personal information about individuals. This can be a privacy concern, as it can lead to people’s personal information being exposed without their consent.

Conclusion

Generative AI is a powerful technology with the potential to do a lot of good in the world. However, it is important to use this technology responsibly. By following the principles of transparency, fairness, accuracy, accountability, and privacy, we can ensure that generative AI is used for good and not for harm.

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Jayita Bhattacharyya

Official Code-breaker | Generative AI | Machine Learning | Software Engineer | Traveller