IMPACT OF AI WILL CHANGE THE WORLD

Innovations in the field of artificial intelligence continue to shape the future of humanity across nearly every industry. AI is already the main driver of emerging technologies like big data, robotics and IoT, and generative AI has further expanded the possibilities and popularity of AI.

AI has come a long way since 1951, when the first documented success of an AI computer program was written by Christopher Strachey, whose checkers program completed a whole game on the Ferranti Mark I computer at the University of Manchester. Thanks to developments in machine learning and deep learning, IBM’s Deep Blue defeated chess grandmaster Garry Kasparov in 1997, and the company’s IBM Watson won Jeopardy! in 2011.

AI’s ability to analyze massive amounts of data and convert its findings into convenient visual formats can also accelerate the decision-making process. Company leaders don’t have to spend time parsing through the data themselves, instead using instant insights to make informed decisions.

Business automation has naturally led to fears over job losses. In fact, employees believe almost one-third of their tasks could be performed by AI. Although AI has made gains in the workplace, it’s had an unequal impact on different industries and professions. For example, manual jobs like secretaries are at risk of being automated, but the demand for other jobs like machine learning specialists and information security analysts has risen.

Workers in more skilled or creative positions are more likely to have their jobs augmented by AI, rather than be replaced. Whether forcing employees to learn new tools or taking over their roles, AI is set to spur upskilling efforts at both the individual and company level. “One of the absolute prerequisites for AI to be successful in many [areas] is that we invest tremendously in education to retrain people for new jobs,” said Klara Nahrstedt, a computer science professor at the University of Illinois at Urbana–Champaign and director of the school’s Coordinated Science Laboratory.

Companies require large volumes of data to train the models that power generative AI tools, and this process has come under intense scrutiny. Concerns over companies collecting consumers’ personal data have led the FTC to open an investigation into whether OpenAI has negatively impacted consumers through its data collection methods after the company potentially violated European data protection laws.

In response, the Biden-Harris administration developed an AI Bill of Rights that lists data privacy as one of its core principles. Although this legislation doesn’t carry much legal weight, it reflects the growing push to prioritize data privacy and compel AI companies to be more transparent and cautious about how they compile training data.

AI could shift the perspective on certain legal questions, depending on how generative AI lawsuits unfold in 2024. For example, the issue of intellectual property has come to the forefront in light of copyright lawsuits filed against OpenAI by writers, musicians and companies like The New York Times. These lawsuits affect how the U.S. legal system interprets what is private and public property, and a loss could spell major setbacks for OpenAI and its competitors.

Ethical issues that have surfaced in connection to generative AI have placed more pressure on the U.S. government to take a stronger stance. The Biden-Harris administration has maintained its moderate position with its latest executive order, creating rough guidelines around data privacy, civil liberties, responsible AI and other aspects of AI. However, the government could lean toward stricter regulations, depending on changes in the political climate.

On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Optimists can view AI as a way to make supply chains more efficient, carrying out predictive maintenance and other procedures to reduce carbon emissions.

At the same time, AI could be seen as a key culprit in climate change. The energy and resources required to create and maintain AI models could raise carbon emissions by as much as 80 percent, dealing a devastating blow to any sustainability efforts within tech. Even if AI is applied to climate-conscious technology, the costs of building and training models could leave society in a worse environmental situation than before.

In an essay about the future potential of AI, Anthropic CEO Dario Amodei hypothesizes that powerful AI technology could speed up research in the biological sciences as much as tenfold, bringing about a phenomenon he coins “the compressed 21st century,” in which 50 to 100 years of innovation might happen in the span of five to 10 years. This theory builds on the idea that truly revolutionary discoveries are made at a rate of maybe once per year, with the core limitation being a shortage of talented researchers. By increasing the cognitive power devoted to developing hypotheses and testing them out, Amodei suggests, we might close the time gap between important discoveries like the 25-year delay between CRISPR’s discovery in the ‘80s and its application to gene editing.