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According to Autonomy Think Tank, automating jobs with large language models ( LLMs) could result in significant time savings without sacrificing pay or productivity, but achieving the advantages of artificial intelligence ( AI)-driven productivity gains in this way will require coordinated political action.

In a paper published on November 20, 2023, Autonomy predicted that, if LLMs are used properly, 8.8 million UK workers could have four-day workweeks by 2033, while just under 28 million could see their working hours cut by 10 % in the same period.

Although the latter scenario does not necessarily entail a four-day work week for the majority of people, it would still represent egregious changes in the world of work, according to Autonomy, which noted that this would represent 28 and 88 % of the UK’s roughly 32 million-strong workforce, respectively.

It was further stated that there are substantial opportunities for local authorities in certain, with 44 authorities potentially having at least one-third of their workforce eligible for a four-day workweek by 2033 across England and Wales. 18 of these regional authorities are based in London.

Will Stronge, the director of research for Autonomy, stated that” Our research offers a new perspective in debates around how AI can be used for good.” A shorter workweek is the most concrete way to guarantee that Artificial benefits both employees and businesses, according to &nbsp. A new era of four-day working weeks for everyone should be ushering in if AI is to be implemented quite across the economy.

Autonomy noted that despite the fact that people have long predicted and anticipated shorter working weeks brought on by technological advancements, historic increases in productivity over the past few decades have not resulted in improved wealth or leisure time for the majority of people, mostly as a result of financial inequality.

It claimed that there is frequently a pessimism surrounding AI-driven productivity gains, with most conversations emphasizing the possibility of job losses and worsening working conditions, but that for gains could also be used to give some people shorter working weeks while maintaining their pay and performance.

It stated that such a policy has the potential to prevent common unemployment ( and all of its social and political repercussions ), to lessen the prevalence of physical and mental illnesses brought on by overwork, and to significantly increase the amount of free time available for democracy, leisure time, or social cohesion in general.

These functioning factors cannot be emphasized much when it comes to the productivity question in the UK, where work-related stress, anxiety, and depression constitute one of the most important labor market issues today. Therefore, outside of the AI-augmentations we have modelled, we can anticipate a great deal of additional productivity-enhancing side effects from the shorter work week.

It continued by saying that a past UK trial of the four-day work week, which resulted in the majority of companies involved deciding to continue with shorter weeks permanently, demonstrated that many businesses simply do not need to spend extra money or lose productivity when shifting staff to shorter hours, especially if their job is desk-based.

It stated that” the benefits of work process reorganization and evaluation, better staff health, improved staff loyalty, fewer sick days, and greater retention accrued through better work-life balance give a significant boost to performance.”

However, Autonomy makes it clear that productivity gains depend on “geographic, demographics, economic cycle, and other fundamental job market factors” like workers ‘ access to collective bargaining and are not always distributed equally between employers and employees.

This essay identifies an opportunity rather than a fate. According to the report, wage levels, government policy, levels of sector monopolization, trade union density, and other factors are to blame for the unevenness of technology’s real diffusion and adoption.

It goes without saying that a strong commercial strategy that spans national, provincial, and municipal levels and implements incentives and regulations for the personal sector is necessary for widespread adoption of these new AI technologies.

Most important, workplace technologies are cultural and social technologies, so worker voice—those who will be utilizing and cooperating with these tools—will be crucial.

Autonomy advises establishing “automation hubs,” supported by trade union and industry agreements, to increase the adoption of LLMs in ways that are both equitable and result in a reduction in working time, in order to deliver good AI-led changes for workers and not merely employers.

Through whatever economic and incentive options are available,” These hubs would also aim to increase adoption in sectors that have seen low-investment,” it said. Each branch, possibly at the local authority level, would have specialized knowledge regarding the nature of the work in question and the Artificial technology that is most pertinent. These hubs could have branches for each employment sector.

Others have even discussed the conflict between the advantages of AI and the obvious problems with who these advantages are distributed to, similar to Autonomy.

For instance, in its second session, the House of Lords heard from witnesses about the power disparities between governments and technology developers before launching &nbsp, an investigation into the risks and opportunities presented by LLMs. &nbsp,

Dan McQuillan, a lecturer in artistic and cultural computing, also emphasized the dangers of outsourcing decision-making processes to such AI tools in his andnbsp, written evidence for the inquiry.

The biggest danger that big language models pose is using them to address fundamental structural issues in the economy and in important state functions like welfare, education, and healthcare, he wrote.

The misrepresentation of these technologies makes it attractive for institutions to adopt them in order to protect public services from ongoing austerity and rising demand, as well as for businesses to believe they can recover short-term profitability by replacing workers with huge language models.

The question is,” By the time this becomes distinct, how many of our current systems will have been replaced by huge language models, and what will be the long-term effects of that?”

The technology will be “used as an opportunity to transform social systems without political debate,” McQuillan continued, adding that the net effect of LLM deployments within the current balance of cultural forces “is the acceleration of precaritization, outsourcing, and privatization.”

The Ada Lovelace Institute reviewed the use of AI foundation models ( including LLMs) in the UK public sector in October 2023, noting that the technology could be used for things like document analysis, decision-making support, and customer service enhancement.

The Ada Lovelace Institute also outlined the benefits of using AI in this way, including improved domestic knowledge management within the government, more individualized and available government communications tailored to individual needs, and increased efficiency in the delivery of public services.

While there is optimism about the potential of these systems in both the people sector and industry, especially in the face of tightening fiscal restraints and growing user needs, the institute noted that there are also real risks associated with issues like bias and discrimination, privacy breaches, misinformation, security, over-reliance on industries, workforce harms, and uneven access.

It went on to say that there is a chance that these models will be adopted by the public sector because they are cutting-edge technology more than the best available remedy. &nbsp,

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