Generative AI has the potential to revolutionize the world, transforming social, cultural, and economic structures in ways that we can’t yet imagine. However, with this great power comes great responsibility, and it’s essential to ensure that innovation doesn’t outpace accountability. New regulatory guidance must be developed at the same rate as the launch of new AI applications to prevent the irresponsible use of this technology. To fully understand the moral conundrums around generative AI, we must take a step back to understand these large language models, how they can create positive change, and where they may fall short.

How Generative AI Works

Unlike humans, who answer questions based on our genetic makeup, education, self-learning, and observation, generative AI has access to the world’s data at its fingertips. However, just as human biases influence our responses, AI’s output is biased by the data used to train it. Because data is often comprehensive and contains many perspectives, the answer that generative AI delivers depends on how you ask the question. AI can be programmed to make its output more precise, but it’s important to consider the consequences when using this technology to make decisions that affect humans’ lives.

Low-Risk Applications of Generative AI

Low-risk, ethically warranted applications will almost always focus on an assistive approach with a human in the loop, where the human has accountability. For instance, if ChatGPT is used in a university literature class, a professor could make use of the technology’s knowledge to help students discuss topics at hand and pressure-test their understanding of the material. Here, AI successfully supports creative thinking and expands the students’ perspectives as a supplemental education tool — if students have read the material and can measure the AI’s simulated ideas against their own.

Medium-Risk Applications of Generative AI

Some applications present medium risk and warrant additional criticism under regulations, but the rewards can outweigh the risks when used correctly. For example, AI can make recommendations on medical treatments and procedures based on a patient’s medical history and patterns that it identifies in similar patients. However, a patient moving forward with that recommendation without the consult of a human medical expert could have disastrous consequences. Ultimately the decision — and how their medical data is used — is up to the patient, but generative AI should not be used to create a care plan without proper checks and balances.

High-Risk Applications of Generative AI

High-risk applications are characterized by a lack of human accountability and autonomous AI-driven decisions. For example, an “AI judge” presiding over a courtroom is unthinkable according to our laws. Judges and lawyers can use AI to do their research and suggest a course of action for the defense or prosecution, but when the technology transforms into performing the role of judge, it poses a different threat. Judges are trustees of the rule of law, bound by law and their conscience — which AI does not have. There may be ways in the future for AI to treat people fairly and without bias, but in our current state, only humans can answer for their actions.

Preparing for the Impact of Generative AI

To minimize immediate risk, there are four steps we can take now:

Self-governance:

Every organization should adopt a framework for the ethical and responsible use of AI within their company. Before regulation is drawn up and becomes legal, self-governance can show what works and what doesn’t.

Testing:

A comprehensive testing framework is critical — one that follows fundamental rules of data consistency, like the detection of bias in data, rules for sufficient data for all demographics and groups, and the veracity of the data.

Responsible action:

Human assistance is important no matter how “intelligent” generative AI becomes. By ensuring AI-driven actions go through a human filter, we can ensure the responsible use of AI and confirm that practices are human-controlled and governed correctly from the beginning.

Continuous risk assessment:

Considering whether the use case falls into the low, medium, or high-risk category will help determine the appropriate guidelines that must be applied to ensure the right level of governance.

Generative AI has the potential to change the world, but it’s important to consider the ethical and moral implications of its use. With the technology advancing at such a rapid pace, it’s essential to take steps to minimize risk and ensure that innovation is guided by accountability. By implementing frameworks for self-governance, comprehensive testing, responsible action, and continuous risk assessment, we can prepare for the impact of generative AI and ensure that it’s used to create positive change in the world.

AI

Articles You May Like

The Impact of the Inflation Reduction Act on Clean Energy and Manufacturing in the U.S.
Unveiling the Future: VentureBeat’s Commitment to Deep Insights and Special Issues
Critical Analysis: OpenAI’s GPTBot and the Ethics of Web Scraping
A Glimpse into the New and Improved X: Elon Musk’s Ongoing Twitter Revamp

Leave a Reply

Your email address will not be published. Required fields are marked *