Ethical use of Generative AI

By Dr Abhinanda Sarkar, Director Academics, Great Learning

There is plenty of chatter around generative AI, most of it around the multifaced nature of ChatGPT. The chatbot has made a quantum jump, now capable of things that once required human intervention.

Generative AI can manufacture and produce content across several domains; the technology is seemingly inescapable. And between the textual applications of ChatGPT and graphical uses of DALL-E, the space is ripe for misuse—ChatGPT is accused of writing school essays and even generating music and passing it off as an artist’s original work. And that’s just the tip of the iceberg. Additionally, questions around tech autonomy raise further concerns and highlight the inherent risks associated with generative AI, prompting precautions and ethical usage of the tech.

The debate concerning ethics and AI has been ongoing for several decades: As generative AI spreads and modern computing intelligence blurs the lines between fiction and reality, people must use the tools in good faith and avoid manipulating technology to affect individuals, companies, and even society, possibly impacting privacy and data to a large degree.

People and organisations must utilise generative AI with care and consider a few ethical guidelines along the way:

• Overcoming the issue of reliability: It is essential to understand that AI responses are not always necessarily valid. Insufficient or biased training data could lead to apparently confident answers that don’t hold up to scrutiny. Large language models build statements with many successive guesses rooted in unclear sources—ChatGPT is guilty of providing results with an air of infallible authority, turning out to be cases of misplaced confidence. Choosing alternative models that either trace back to multiple sources or express doubt over their answers could prove a better bet at establishing reliability and giving users context. And when being used to generate code, programmers should check the output before incorporating it instead of unthinkingly trusting whatever is churned out.

• Regard information with caution: Generative AI learns from online data—from more respected sources like online journals to less convincing places like blogs. As such, its training data is not always exact or precise. Large amounts of data cannot be verified, comes from untrusted sources, or contains bias. While curation can limit unwanted content, it is currently possible to bypass that. Consequentially, generative AI responses could perpetuate dubious information filled with hate speech, racism, or misconstrued truths. From an industry standpoint, more advanced measures are required, including stricter curation protocols. On the other hand, casual users need to be aware of this factor and corroborate information without taking statements at face value.

• Tread carefully over copyrighted material: Generative AI tools have a massive repository of media they train on—they can use these existing texts and images of human authors to generate responses, offering up prose and art that, while distinct in a sense, owes a lot to the original creators. This leads to vagueness around ownership laws and attribution since the field is relatively new, and what constitutes “ownership” is a murky region. Organisations must also be careful when using generative AI for high-stakes business operations, as tracing the data to its source could be impossible, leaving the possibility of infringing upon another company’s intellectual property open. People and enterprises must err on the side of caution until there is more clarity around AI and copyright law.

• Using technology as it’s intended: While the discussion of sentience and intent around AI rages on, what mustn’t be in doubt is the human goal behind its operation. Evidently, any technology in the wrong hands will prove troublesome. With generative AI, there are numerous avenues by which bad actors could propagate harmful material or resort to malicious behaviour. Whether it is using the technology to manipulate a person’s image, art, music, or writing for the purpose of scamming people out of their money or creating fake speeches to circulate misinformation far and wide, the scope for disseminating false content under the guise of authority is undeniable. Companies and individuals must shoulder careful responsibility when working with generative AI—leaning into it with empathy and proper purpose—while staying alert so they’re not at the receiving end.

Technology isn’t intrinsically malicious. But AI does raise some more interesting questions around that statement and is a grey area requiring sensitive thought. There is definitely the need to govern how AI is deployed and balance it against a human perspective while ensuring it is used in a fair manner and doesn’t break the law. It is critical that innovation doesn’t happen at the expense of propriety and human well-being, and the onus is on the people using these tools to exercise the utmost prudence until a time comes when we can make further advancements in the field.

AIChatGPTGenerative AI
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