Based on an analysis of the definitions of the Future of Work, it is evident that there are several predominant trends, themes, concepts, and technologies that shape our understanding of this topic. At a high level, these include technology, climate change, globalization, and demographic changes. At a more granular level, there are various specific trends such as supply chain optimization, outsourcing, aging populations, increased migration and mobility, and a greater emphasis on work-life balance and wellness.

The role of Covid-19 and future pandemics has also become a prominent concern in discussions about the Future of Work. It is important to note that the focus on technology often overlooks its social context, as remarked by Paul Deane (2021). The literature on the Future of Work has predominantly focused on the impact of digitalization, automation, and analytics, particularly in the context of Artificial Intelligence (AI). However, there is often a lack of distinction between narrow task-focused AI and more wide-ranging artificial general intelligence (AGI).

Academic research on the Future of Work covers various themes, including workplace relations, workplace changes, diversity, and personal skills. It is crucial to understand that this research provides snapshots of an ever-evolving process. The thematic evolution of Future of Work research has been analyzed over different periods, confirming the consistency of key themes throughout the years.

In addition to thematic analysis, Future of Work research has also been categorized into four dimensions: technological, social, economic, and political/institutional. Technologies like automation, digitalization, platformization, and AI have not only created new forms of work (such as gig work) but also enabled flexible work arrangements (such as remote working). Algorithmic management, driven by AI, has also introduced new management practices that require new types of skills.

The impact of technology on work has broader implications for society and individuals. Concerns have been raised about the social dimension of the Future of Work, including social cohesion and work-life conflicts. Innovations like remote working and gig work may exacerbate these issues and impact career development, job satisfaction, and employee voice. There is a need to balance efficiency and productivity gains with fair wages, working conditions, and job security.

Different perspectives exist regarding the impact of technology on jobs and the economy. Some argue that technological advancements will lead to job losses, wage inequality, and job polarization, while others suggest that technology will create new jobs and augment human capabilities. The economic dimension of the Future of Work is complex, as its impact varies at different levels, from the economy as a whole to individual workers.

The Future of Work encompasses a range of trends, themes, and implications that are interconnected. It is crucial to consider the social, economic, and technological aspects when discussing its impact on individuals, organizations, and societies as a whole.

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The Future of Work: Trends, Themes, and Implications - Fagen wasanni

OpenAI launched ChatGPT 3.5 in November 2022 and, sincethen, it set growth records as it spread like wildfire. Today, itnears one billion unique visitors per month. Since its launch, theworld has been all-consumed with talking about AI and its potentialuse cases across a wide range of industries. Sam Altman, co-founderand CEO of OpenAI, has said that AI tools can find solutions to"some of humanity's biggest challenges, like climatechange and curing cancer".

There has also been plenty of talk about the largest techcompanies (namely Google and Meta, as well as Microsoft) and theirrace in the pursuit of Artificial General Intelligence (AGI). Thismakes it sound very much like an arms race and this is a comparisonthat many have made. Within any race, there's often the concernthat those in the race will cut corners and, in this particularrace, many fear that the consequences could be disastrous. Withinthis article, we explore the possible consequences and the UK'sstance on the regulation of AI to help safeguard against these.

AI is seen as central to the government's ambition to makethe UK a science and technology superpower by 2030 and PrimeMinister Rishi Sunak again made this clear in his opening keynoteat June's London Tech Week: "If our goal is to make thiscountry the best place in the world for tech, AI is surely one ofthe greatest opportunities for us".

As discussed here, AI was also a headline feature earlier thisyear in the government's Spring Budget. Both within this Budgetand since then, the following has been announced:

Despite the many potential benefits of AI, there is also growingconcern about the risks of AI, ranging from the widely discussedrisk of disinformation to the evolving risk of cybersecurity. Acouple of the widely discussed risks of AI include:

Misinformation and bias

Most AI tools will use Large Language Models (LLM), whicheffectively means that they are trained on large datasets, mostlypublicly available on the internet. So it stands to reason thatthese tools can only be as good as the data they're trained on,but if this data isn't carefully vetted, then the tools will beprone to misinformation and even include bias, as we saw withTwitter's infamous chatbot, Tay, which quickly began to postdiscriminatory and offensive tweets.

AI alignment is a growing field within AI safety that aims toalign the technology with our (ie. human) goals. Therefore, AIalignment is critical to ensuring that AI tools are safe, ethicaland align with societal values. For example, Open AI has stated"Our research aims to make AGI aligned with human values andfollow human intent".

Protecting jobs and economic inequality

Sir Patrick Vallance, the UK's former Government ChiefScientific Adviser, warned earlier this year that "there willbe a big impact on jobs and that impact could be as big as theIndustrial Revolution was". This isn't an uncommon vieweither, recently Goldman Sachs predicted that roughly two-thirds ofoccupations could be partially automated by AI. More worryingly,IBM's CEO Arvind Krishna predicted that 30% ofnon-customer-facing roles could be entirely replaced by AI andautomation within the next five years, which equates to 7,800 jobsat IBM. Job displacement and economic inequality is a huge risk ofAI.

Many have warned of other risks such as privacy concerns, theconcentration of power and even existential risks. As this is afast-evolving industry, you could also argue that, as we don'tyet fully understand what AI could look like and be used for in thefuture, we also don't yet know all of the risks that the futurewill bring.

Despite talking about the potential benefits of AI, ranging fromsuperbug-killing antibiotics to agricultural use and potential infinding cures for diseases, Rishi Sunak also recognised thepotential dangers, saying "The possibilities areextraordinary. But we must, and we will, do it safely. I knowpeople are concerned". Keir Starmer, also at London Tech Week,continued this theme by saying "we need to put ourselves intoa position to take advantage of the benefits but guard against therisks" and called for the UK to "fast forward" AIregulation.

Rishi Sunak also went on to say that "the very pioneers ofAI are warning us about the ways these technologies could undermineour values and freedoms, through to the most extreme risks ofall". This could be a reference to multiple pioneers,including:

Despite the calls, it should also be acknowledged that AI isextremely difficult to regulate. It is constantly evolving so itbecomes difficult to predict what it will look like tomorrow and assuch, what regulation needs to look like to not become quicklyobsolete. The fear for governments, and the pushback from AIcompanies, will be that overregulation will stifle innovation andprogress, including all the positive impacts that AI could have, soa balance must be struck.

Earlier this year, it seemed that the UK's stance onregulation was to be a very hands-off approach and this would belargely left to existing regulators and the industry itself bytaking a "pro-innovation approach to AI regulation"(which was the name of the white paper initially published on 29March 2023). Within this White Paper, unlike the EU, the UK'sGovernment confirmed that it wasn't looking to adopt newlegislation or create a new regulator for AI. Instead, it wouldlook to existing regulators like the ICO (InformationCommissioner's Office) and the CMA (Competition and MarketsAuthority) to "come up with tailored, context-specificapproaches that suit the way AI is actually being used in theirsectors". This approach was criticised by many, including KeirStarmer who commented that "we haven't got an overarchingframework".

However, since this white paper (which has since been updated),Rishi Sunak has shown signs that the UK's light-touch approachto regulation needs to evolve. At London Tech Week, he stated thathe wants "to make the UK not just the intellectual home butthe geographical home of global AI safety regulation". Thiswas coupled with the announcement that the UK will host a globalsummit on safety in artificial intelligence this autumn where,according to a No. 10 spokesman, the event will "provide aplatform for countries to work together on further developing ashared approach to mitigate these risks".

100m has also been announced for the UK's AIFoundation Model Taskforce, with Ian Hogarth, coauthor of theannual State of AI report, announced to lead this task force. Thekey focus for this Taskforce will be "taking forwardcutting-edge safety research in the run-up to the first globalsummit on AI".

Time will tell on both the potential (both good and bad) for AIand how the regulation within the UK and globally rolls out, butit's clear that the UK wants to play a leading role in bothregulation and innovation, which may at times clash with eachother. In an interview to the BBC on AI regulation, Sunak said"I believe the UK is well-placed to lead and shape theconversation on this because we are very strong when it comes toAI". If you want to discuss the benefits of AI for yourspecific business situation, please contact James or get in touchwith your usual UHY adviser.

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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What Lies Ahead For AI In The UK? - New Technology - UK - Mondaq News Alerts

Erik McGregor/LightRocket via Getty Images

The alarm bells have been rung. In May, computer scientist Geoffrey Hinton, known as the godfather of AI, quit his role at Google to warn of the existential threat posed by artificial intelligence. The Center for AI Safety followed up with an open letter, signed by Hinton and hundreds of others, warning that advanced AI could destroy humanity. Mitigating the risk of extinction from AI should be a global priority, read the statement.

This sudden surge of concern seems to have been motivated by the rapid advance of AI-powered chatbots like ChatGPT and the race to build more powerful systems. The fear is that the tech industry is recklessly accelerating the escalation of AIs capabilities. All of which sounds scary.

But the warnings are also suspiciously vague. When you scrutinise the scenarios typically put forward for precisely how AI could wipe out humans, it is hard to avoid the conclusion that such fears arent well-founded. Many experts are instead warning that fretting over long-term doomsday scenarios is a distraction from the immediate risks posed by existing AIs.

Generally, the people who talk about existential risks reckon that we are on a trajectory towards artificial general intelligence (AGI), roughly defined as machines that can out-think humans. They predict that people will invest advanced AIs with more autonomy, giving them access to vital infrastructure, such as the power grid or financial markets, or even putting them at the forefront of warfare at which point they could go rogue or otherwise resist our attempts to control them.

But it remains to be seen if AIs will ever reach the kind of super-intelligence

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Forget human extinction these are the real risks posed by AI today - New Scientist

A radiologist at Unfallkrankenhaus Berlin uses anAI-based app to look at a patients brain scan images on a tablet. (Monika Skolimowska/picture alliance via Getty Images)

Pew Research Center conducted this study to understand how American workers may be exposed to artificial intelligence (AI) at their jobs. The study emphasizes the impact of AI on different groups of workers, such as men and women and racial and ethnic groups, and it includes new survey findings on how American adults think AI will impact them personally, setting it apart from preceding analyses.

By exposure to AI, we refer to the likelihood that the activities workers perform on their jobs may be replaced or aided by artificial intelligence. We make no determination as to whether workers may lose their jobs as a result or gain new jobs, and we also do not consider the role of robots.

Most of the analysis is based on data from the Occupational Information Network (O*NET), Version 27.3. O*NET analysts rate the importance of 41 work activities related to job performance in individual occupations. We grouped these activities into three categories based on their likely exposure to AI: low exposure, medium exposure and high exposure. Occupations were ranked by the relative importance of low- or high-exposure activities. Those in the top quarter of each ranking are the least or most exposed occupations. The remaining occupations have medium exposure.

Data on the employment and earnings of workers in individual occupations and their demographic profiles are from the Current Population Survey (IPUMS). Monthly files from January to December 2022 were combined to form an annual file. Earnings data is available for a quarter of this sample. The AI-exposure rankings of 873 detailed occupations from the O*NET data are matched to 485 broader occupations listed in the CPS.

A part of the analysis is based on a Pew Research Center survey of 11,004 U.S. adults conducted from Dec. 12 to 18, 2022. Everyone who took part in the survey is a member of the Centers American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way, nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATPs methodology.

Here are the questions used for this report, along with responses, and its methodology.

Artificial intelligence (AI): Broadly speaking, AI refers to a range of applications of machine learning, computer vision and natural language processing that allow computers or machines to perform tasks autonomously. AI can substitute for or complement a variety of human tasks, such as writing, drawing, providing customer service, reading radiology scans, driving cars and more. ChatGPT and Dall-E are examples of AI-driven technologies.

Low or high exposure to AI: We rated a set of 41 job-related work activities common to all occupations as having low, medium or high exposure to AI. How much an occupation is exposed to AI depends on which of these work activities is more important in that particular job. The importance scale runs from one (not important) to five (extremely important). In this report, we focus on the importance of low- and high-exposure activities. In one step of analysis, occupations are ranked by the relative importance of high-exposure activities in them; the jobs ranking in the top 25% are occupations that we rate as most exposed to AI. In another step, occupations are ranked by the relative importance of low-exposure activities in them. Those ranking in the top 25% are occupations that are least exposed to AI. A full description of the ranking process is in the methodology.

The terms occupation and job are often used interchangeably in the report, as are the terms earnings and wages.

White, Black, Asian and American Indian or Pacific Islander workers include those who report being only one race and are not Hispanic. Hispanics are of any race.

High school graduate refers to those who have a high school diploma or its equivalent, such as a General Education Development (GED) certificate, and those who had completed 12th grade, but their diploma status was unclear (those who had finished 12th grade but not received a diploma are excluded). Adults with some college include those with an associate degree and those who attended college but did not obtain a degree.

U.S. born refers to individuals who are U.S. citizens at birth, including people born in the 50 U.S. states, the District of Columbia, Puerto Rico or other U.S. territories, as well as those born elsewhere to at least one parent who is a U.S. citizen. The terms foreign born and immigrant are used interchangeably in this report. They refer to people who are not U.S. citizens at birth.

Artificial intelligence (AI) recently gained new attention with the release of ChatGPT and Dall-E. These tools and the broader array of AI-driven business applications represent a new reality for workers.

Historically, changes in technology have often automated physical tasks, such as those performed on factory floors. But AI performs more like human brainpower and, as its reach grows, that has raised questions about its impact on professional and other office jobs questions that Pew Research Center seeks to address in a new analysis of government data.

Which jobs are more exposed to AI? Work-related tasks vary in their exposure to AI. Some activities, such as repairing equipment, may have low exposure to AI, while others may have a medium or a high degree of exposure. Also, activities with different levels of exposure may be equally important within many jobs.

In our analysis, jobs are considered more exposed to artificial intelligence if AI can either perform their most important activities entirely or help with them.

For example, AI could replace, at least to a degree, the tasks getting information and analyzing data or information, or it could help with working with computers. These are also among the key tasks for judicial law clerks and web developers, and they are more exposed to AI than other workers. However, AI alone cannot assist and care for others or perform general physical activities. Thus, nannies for whom these are essential activities are less exposed to AI.

In our analysis, jobs that placed in the top 25% when ranked by the importance of work activities with high exposure to AI were judged to be the most exposed. Jobs that placed in the top 25% when ranked by the importance of work activities with low exposure to AI are the least exposed. The remaining jobs, such as chief executives, are likely to see a medium level of exposure to AI. (Refer to the appendix for an extended list of examples of occupations in each group.)

Related: How we determined the degree to which jobs are exposed to artificial intelligence

Will exposure to AI lead to job losses? The answer to this is unclear. Because AI could be used either to replace or complement what workers do, it is not known exactly which or how many jobs are in peril. For this reason, our study focuses on the level of exposure jobs have to AI. It sets aside the question of whether this exposure will lead to jobs lost or jobs gained.

Consider customer service agents. Evidence shows that AI could either replace them with more powerful chatbots or it could enhance their productivity. AI may also create new types of jobs for more skilled workers much as the internet age generated new classes of jobs such as web developers. Another way AI-related developments might increase employment levels is by giving a boost to the economy by elevating productivity and creating more jobs overall.

Overall, AI is designed to mimic cognitive functions, and it is likely that higher-paying, white-collar jobs will see a fair amount of exposure to the technology. But our analysis doesnt consider the role of AI-enabled machines or robots that may perform mechanical or physical tasks. Recent evidence suggests that industrial robots may reduce both employment and wages. Moreover, jobs held by low-wage workers, those without a high school diploma, and younger men are more exposed to the effects of industrial robots.

What data did we use? This analysis rests on data on the importance of 41 essential work activities in 873 occupations from the U.S. Department of Labors Occupational Information Network (O*NET, Version 27.3). We used our judgment to determine which of these activities have low, medium or high exposure to AI, but focus on the importance of low- and high-exposure activities. For additional analysis, the 873 occupations were further grouped to a total of 485 for which government data on employment and earnings of workers were available. That allowed us to analyze the potential impact of AI on different groups of workers. Other findings about how workers feel about AI come from a Center survey of 11,004 U.S. adults conducted between Dec. 12 and 18, 2022. (Refer to the text boxes and methodology for more details.)

In our analysis, we considered two major questions when assessing the exposure of jobs to AI:

The O*NET database lists a set of 41 work activities in common across all occupations. Examples of these activities are getting information, selling or influencing others, and handling and moving objects (refer to the methodology for the complete list). We used our collective judgment to designate each activity as having high, medium or low exposure to AI. Consensus on some activities, such as performing general physical activities or processing information, was reached quickly. The former is judged as having low exposure to AI and the latter is judged as having high exposure.

In other instances, we used additional details on a work activity to reach consensus. The question we asked ourselves at this stage was the following:

Are most of the detailed tasks that comprise a work activity exposed to AI?

For example, the job activity performing for or working directly with the public is ambiguous on the surface. But consider the list of detailed tasks that comprise this broad activity:

The consensus we reached was that most of these detailed tasks, such as interfacing with customers or creating music, had a high degree of exposure to AI. Only a few tasks auditioning, comedic or dramatic performances and dancing were considered to have relatively low exposure to AI. For that reason, the broad activity performing for or working directly with the public is deemed to have high exposure to AI.

At the other end of the exposure scale is the work activity coaching and developing others, entailing:

The focus of most of these detailed tasks involves personal interaction. So, we judged that the activity coaching and developing others has low exposure to AI.

Overall, 16 work activities were assessed to have high exposure to AI, 16 more were judged to have medium exposure, and nine were deemed to have low exposure. (Refer to the methodology for where each activity was classified.)

The 41 work activities listed in O*NET are spread across all occupations in the O*NET database. That is to say, each occupation is a mix of low, medium and high AI-exposure activities. The question then is:

Which work activities are relatively more important in a job? Are high- or low-exposure activities more important than other activities?

To answer this, we first estimated the averages of the importance ratings for high-, medium- and low-exposure activities in each job, where the rating of each activity within a category is taken from the O*NET database. The rating for each activity ranges from one (not important) to five (extremely important).

Overall, among the 873 occupations we looked at, high-exposure activities were rated as being important to extremely important in 77% of occupations, and medium-exposure activities were similarly important in 72% of occupations. Low-exposure activities were rated as important in 39% of occupations. This suggests that high, medium and low exposure could simultaneously be important in a job.

The final step was to estimate the relative importance of high-, medium- or low-exposure activities in each job that is, to determine which tasks are more important than the others in any given job. This procedure is described in the methodology. Occupations were then ranked two ways, once by the relative importance of high-exposure work activities and again by the relative importance of low-exposure work activities.

In our analysis, jobs that are most exposed to AI are in the top 25% of occupations ranked by the relative importance of high-exposure activities. Jobs that are least exposed to AI are in the top 25% of occupations ranked by the relative importance of low-exposure work activities. The other jobs may be thought of as having a medium level of exposure to AI. (Refer to the appendix for examples of occupations that are among the most or least exposed or have a medium level of exposure.)

To take an example, consider mechanical drafters, who prepare detailed working diagrams of machinery and mechanical devices. Mechanical drafters are among the workers most exposed to AI. For them, high-exposure activities have an average rating of 3.28 but low-exposure activities have an average rating of 2.36, where a rating of 3 means an activity is important.

For nannies, among the least exposed workers, high-exposure activities have an average rating of 2.36 but low-exposure activities have a rating of 3.03.

Our analysis follows in the footsteps of other researchers who have recently examined the impact of AI on the workplace. Eloundou, Manning, Mishkin and Rock (March 2023) conclude that about one-in-five U.S. workers may see an impact on half or more of their job tasks. Felten, Raj and Seamans (April 2021) find that white-collar occupations requiring advanced degrees are most exposed to AI, as are industries providing financial or legal services. Webb (January 2020) reports that high-skill occupations, highly educated and older workers will be more impacted by AI, but he does not draw conclusions about the nature or the extent of the impact on workers. Our findings are broadly consistent with the results of these analyses.

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Which US workers are exposed to AI in their jobs? - Pew Research Center

As part of our AItopia series exploring how AI will impact architecture and design, Dezeen examines whether the technology will end up taking architects' jobs.

In 2019, New York-based designer Sebastian Errazuriz caused a stir with his claim that 90 per cent of architects could lose their jobs to machines.

Four years on, following the emergence of several generative-AI models such as Midjourney and ChatGPT, Errazuriz is writing a book about AI's impact on society and told Dezeen his opinion has not changed.

"It's an enormous issue that we need to try and deal with," he said."People always say, 'but isn't AI just another tool?' Right now it looks like a tool, but the tool is getting really good, really fast and the purpose of this tool is to think for itself."

He claims that well-known architects who mocked his warnings in 2019 have recently conceded privately that he was right.

Architecture at high risk of automation

Investment bank Goldman Sachs made headlines in March with its prediction that AI could replace the equivalent of 300 million jobs globally across all industries.The researchers estimated that 37 per cent of architecture and engineering work tasks "could be automated by AI", placing it among the most-exposed industries.

And this month, the Organisation for Economic Co-operation and Development echoed the warnings about job losses in skilled professions.

A survey conducted by design technology firm RevitGods found that 55 per cent of US architects are "moderately concerned" about being replaced by AI in the future, with a further 20 per cent "very concerned".

But not everyone shares Errazuriz's pessimism. Among them is Phillip Bernstein, associate dean and professor adjunct at the Yale School of Architecture who previously held senior roles at software firm Autodesk and Pelli Clarke Pelli Architects and has authored a book on architecture and AI.

"I have been around long enough to see multiple waves of technological change in the industry and this argument happens every single time," Bernstein told Dezeen.

"It happened during CAD [computer-aided design], it happened during BIM [building information modelling], and now it's happening with AI," he added. "We somehow always seem to survive these things."

The Dezeen guide to AI

Bernstein argues that even the best AIs are still nowhere near the competence of a qualified architect.

"I happen to think that what we do as architects is pretty complicated," he said."At it's best, it's about managing a complex, multi-variable problem and making a series of ambiguous judgements that require trade-offs, and I don't believe we will get to a model that can do even 10 per cent of that in the foreseeable future."

"If we're not even at the point where a car can drive itself, I think we're a long way from the point where an algorithm can be a professional architect," he continued.

"Our current traditional methodology will radically change"

The possible emergence of artificial general intelligence in the future a hotly debated topic would likely upend all intellectual industries and much of our current society.

For now, most people's idea of AI architecture is likely the dreamlike, eerily real-looking visualisations created with text-to-image models such as Midjourney.However, AI tools created specifically for use in architecture and design are beginning to enter the market.

Combined, the most advanced of these can generate massing images, floor plans, cost analyses, material specifications and technical drawings though none can yet do it all.

In a recent interview with Dezeen, the co-founder and CEO of one of the leading systems, LookX, dismissed the idea that it could replace architects.

Instead, Wanyu He argued, AI "will liberate us from repetition and allow us to concentrate on things with added value to society".

In particular, he claims it will dramatically speed up the feasibility-testing process, freeing up time to spend on the more creatively rewarding aspects of architecture.

Few have spent more time experimenting with AI-architecture tools than Harvard Graduate School of Design research associate and ArchiTAG co-founder George Guida.He agrees that the technology will not replace architects anytime soon.

"Our current traditional methodology will radically change, but not be substituted," said Guida. "I do think that architects still will need to stay at the centre of being the driver within that process."

"So I think productivity will increase let's say we'll have more time and space to design. I think that the role of the architect will simply have to evolve, but it won't be replaced," he continued.

"It will give smaller firms a stronger edge"

But even if AI is not capable of usurping the human architect outright, could architecture jobs still be lost as the technology is adopted?

"I do think there are large swathes of the work that are potentially automatable by AI," said Bernstein. "So the question is what happens to that additional capacity. Do we use it to do our jobs better, or do we eliminate some of those jobs?"

While both believe that AI could eventually be used by developers to design the simplest, most generic projects in-house, Bernstein and Guida are optimistic that the technology presents an opportunity for architecture studios to command higher fees.

"If I can say to a client that I'm using this tech to do a better job, then maybe I can charge more for my time," said Bernstein.

That could give smaller studios that are quick to adopt AI a chance to compete with bigger firms, argues Guida.

"Increasing productivity gives a great opportunity for emerging practices to bring a competitive edge," he said. "So in the short term it won't remove jobs if anything, it will give smaller firms a stronger edge."

Tim Fu uses "Midjourney for architecture" to transform crumpled paper into starchitect buildings

But Errazuriz remains unconvinced. He thinks the major impact will be at bigger firms, where, he points out, only a small handful of employed architects spend a significant portion of their time on creative work.

He argues the idea that AI will enable all these architects to remain in their jobs and simply spend more time exploring their imaginations is "wishful thinking".

"What will most probably happen is that you just start reducing the size of those architecture studios," he said."Depending on how really good this software gets, in the worst-case scenario they would continue to decrease enormously over a 10-year period."

His comments appear to chime with remarks made earlier this year by Morphosis founder Thom Mayne that AI will lead to a decrease in the number of architects in individual studios to a "more intimate" level.

Wider factors at play

An alternative outcome is that the productivity gains afforded by AI could lead to studios and therefore their employees taking on more projects at once.

Architecture critic Kate Wagner has argued this was the main upshot of CAD, lengthening working hours despite similar hopes in the technology's early days that it could free up time for creativity.

Bernstein hopes that the adoption of AI in architecture won't see history repeat itself.

"It's true that CAD didn't enhance the value proposition of architecture, but it was happening alongside a period of buildings getting much more complex and the design and construction industry getting riskier," said Bernstein.

"So architects were drawing more defensively, and CAD made doing that easier. Now, as we are starting to leverage data about buildings to much greater effect, there is a potential value proposition there."

Saudi-based architect Reem Mosleh, who has made a name for herself as a leading voice on AI design, agrees that other factors will influence how the technology ends up impacting the architecture profession.

For instance, she believes it could reduce overtime in combination with a wider cultural shift away from working long hours.

"After Covid, people's priorities in life have changed drastically," she said. "So I really hope that with AI we could actually have this opportunity to live with better balance."

"You can't run away from it"

Regardless of their opinion on the threat that AI poses to jobs, everyone Dezeen spoke to agreed that architects should be proactively getting to grips with the technology.

"If I were a young practitioner I would be playing with this stuff so I understand it, and if I were a practice I would be giving practitioners time to try it out," said Bernstein.

"You can't run away from it, you need to run towards it," said Errazuriz. "Otherwise you'll be like those people that refuse to have a cell phone. You need to stay up-to-date, checking the latest things that come out and incorporating it into the flow or your team or your own work."

"For now, we're the ones giving the prompts," he added. "And so we need to sort of dig deep into our own creativity, into our storytelling, into why we're doing something."

Mosleh is hopeful that any disruption to architecture jobs will be outweighed by new opportunities opened up by AI.

"Architects who decide not to go beyond their normal practice will definitely be at risk," she said. "If you don't evolve you get replaced, it's nature."

"But at the same time I'm sure that those who are seizing the moment, and taking the opportunity will actually have better jobs and more opportunities."

The main image was created using Dall-E 2.

AItopia

This article is part of Dezeen'sAItopiaseries, which explores the impact of artificial intelligence (AI) on design, architecture and humanity, both now and in the future.

Dezeen In Depth

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Will architects really lose their jobs to AI? - Dezeen