Exploring the Long-Term and Short-Term Risks of Generative AI

Introduction

Generative Artificial Intelligence has emerged, very quickly, as a powerful tool in various domains, enabling machines to generate text, images, and even music. To put that quickness into perspective, it took Open AI’s Chat GPT five days to get to one million users. Five days. Compare that to the next fastest being Instagram, taking two and a half months to get to one million downloads.

While generative AI holds massive potential for positive impact, it is also crucial to understand and think through the potential dangers associated with its development and deployment as companies rapidly accelerate integrating it into products we use everyday. We’ll delve into both the short-term and long-term risks posed by generative AI, shedding light on the ethical, societal, and technological concerns that warrant careful consideration.

Short-Term

In the short term, generative AI poses several immediate challenges that deserve to be addressed. One concern is the potential for misuse and abuse, which has already happened with technology like 11 AI’s voice cloning to essentially spread political propaganda. With that ability to generate highly convincing fake text, images, or videos, there is a risk of spreading disinformation, fake news, and propaganda. Malicious actors could exploit generative AI to manipulate public opinion, deceive individuals, or even frame innocent people for crimes they did not commit. Especially considering there are folks out there who are not adept or even familiar with AI, leaving them easier to convince.

Another short-term danger lies in the ethical implications of generative AI. As AI models are trained on monumental amounts of data, they inherently inherit biases present in the training datasets, which are made by humans. This can lead to the perpetuation of social biases, discrimination, and unfairness when generating content. For instance, if a generative AI model is trained on biased text data, it may produce discriminatory or offensive content, further exacerbating societal divisions. Compare this to the issues that companies like Facebook and YouTube have had in the past (and are still facing) regarding their algorithms suggesting content, pages, and groups that propagate discrimination, false information, and extremism based on users’ viewing that is not directly connected, but is degrees away if they were taken down the wrong path.

Furthermore, there are concerns about the impact of generative AI on employment and the economy. As AI systems become more sophisticated, they could potentially replace human workers in various industries. This could result in significant job displacement, leading to social and economic upheaval if appropriate measures are not taken to address this transition. Workers expected output could be considerably increased with leadership knowing that these tools could essentially boost their productivity, while still keeping the same pay rate. This draws similarities to the industrial landscape of blue collar workers in the 70’s and 80’s. Things like car manufacturing had implemented new tooling and machines that enabled a factory to go from producing 10 cars a day to 100. Even though this happened and expectations were set higher, workers were expected to produce a higher output with the same wages. History repeats.

Long-Term

Looking into the future, long-term dangers associated with generative AI raise even more complex challenges. One primary concern is the potential loss of human creativity and originality. As generative AI becomes more capable of creating art, literature, and music, it raises questions about the uniqueness and value of human creations. What is real and what is not? If AI-generated content becomes prevalent, there is a risk of diminishing human artistic expression and the authenticity of creative works. This could mean less significance and value in human-created work that took time and thought, compared to generative AI-created work that took seconds.

We can’t forget privacy and security. Generative AI models require substantial amounts of data to learn and generate content. This raises concerns about the collection and usage of personal data. We are already encountering this issue of our personal data being collected and misused or used for constant marketing. Instagram ads are becoming oddly specific. If misused or mishandled, this data could lead to significant privacy breaches and invasions of everyday lives. Additionally, there is the risk of adversaries utilizing generative AI to launch sophisticated attacks, such as creating hyper-realistic deepfake videos to manipulate individuals or fabricate evidence.

The potential for AI systems to exceed human-level intelligence raises questions about control and decision-making. If generative AI systems become highly autonomous and independent, there is a risk of losing control over their actions and behavior. Ensuring that AI systems align with human values and objectives becomes crucial to prevent unintended consequences or even existential risks.

To Sum It Up

Generative AI holds so much promise and can supplement creativity, but it also comes with inherent dangers that must be addressed. Not as much by us as individuals as by the companies creating them and our governments, just like everything else. To navigate these risks, it is essential to adopt robust governance frameworks, invest in transparency and accountability, and foster interdisciplinary collaboration to ensure that generative AI is developed and deployed responsibly for the benefit of humanity.