These Are the Best and Worst U.S. Metro Areas for Science, Technology, Engineering, and Mathematics Professionals in 2026

A 2026 study by personal finance website WalletHub ranks the best and worst U.S. metropolitan areas for science, technology, engineering, and mathematics (STEM) professionals.

The analysis, published Jan. 21, 2026, compared the 100 most populous U.S. metropolitan statistical areas using 21 metrics grouped into three categories: Professional Opportunities, STEM-Friendliness, and Quality of Life. Data were drawn from publicly available sources including the U.S. Census Bureau, Bureau of Labor Statistics, National Science Foundation, U.S. Patent and Trademark Office, and other national and private datasets, with figures collected as of Dec. 19, 2025.

According to the study, Boston ranked first overall, followed by Atlanta, Seattle, Pittsburgh, and Austin. 

At the lower end of the rankings, Cape Coral, Florida; Jackson, Mississippi; North Port, Florida; Memphis, Tennessee; and Little Rock, Arkansas ranked among the least favorable metro areas for STEM professionals based on the same criteria.

The study also highlights variation across metros in STEM employment concentration and growth. San Jose, California had the highest share of workers employed in STEM fields, while Providence, Rhode Island recorded the highest recent STEM employment growth. Conversely, several metros ranked low due to smaller STEM workforces or slower growth.

WalletHub explained that where city-level data were missing, state-level information was used to represent metro areas in the rankings.

Overall Rank	Metro Area*	Total Score	Professional Opportunities Rank	STEM-Friendliness Rank	Quality of Life Rank
1	Boston, MA	69.43	3	1	67
2	Atlanta, GA	66.70	7	12	9
3	Seattle, WA	65.42	4	7	35
4	Pittsburgh, PA	65.07	24	13	5
5	Austin, TX	64.78	6	20	10
6	San Francisco, CA	64.26	5	3	61
7	Cincinnati, OH	62.05	15	33	6
8	Salt Lake City, UT	60.77	2	37	23
9	Minneapolis, MN	59.69	22	24	14
10	Orlando, FL	59.61	19	31	11
11	Worcester, MA	58.73	40	5	51
12	Sacramento, CA	58.59	55	10	25
13	San Jose, CA	58.19	10	6	79
14	Washington, DC	58.13	1	35	52
15	Portland, OR	57.48	34	43	7
16	Madison, WI	57.18	29	26	29
17	Hartford, CT	57.14	8	27	16
18	Tampa, FL	56.95	25	32	26
19	San Diego, CA	56.76	35	9	56
20	Chicago, IL	56.73	62	17	17
21	St. Louis, MO	56.35	17	45	24
22	Raleigh, NC	56.16	13	14	62
23	Denver, CO	55.88	9	23	57
24	Columbus, OH	55.53	54	15	30
25	Springfield, MA	54.94	98	2	4
26	Albany, NY	54.32	11	40	13
27	Boise, ID	53.58	23	76	12
28	Los Angeles, CA	52.93	76	4	70
29	Houston, TX	52.54	51	22	42
30	Providence, RI	51.22	42	29	40
31	Baltimore, MD	50.85	16	11	87
32	Dallas, TX	50.71	21	25	71
33	Cleveland, OH	50.68	45	30	53
34	Albuquerque, NM	50.60	39	74	20
35	Spokane, WA	50.41	64	41	28
36	Rochester, NY	50.29	49	36	36
37	New York, NY	49.99	48	8	85
38	Harrisburg, PA	49.91	12	57	15
39	Dayton, OH	49.87	20	66	1
40	Nashville, TN	49.31	30	19	80
41	Greenville, SC	48.68	18	54	18
42	Richmond, VA	48.65	14	56	60
43	Des Moines, IA	48.58	27	87	22
44	Tucson, AZ	48.54	68	59	27
45	Buffalo, NY	48.47	56	39	55
46	Columbia, SC	47.65	32	55	46
47	Omaha, NE	47.49	58	85	21
48	Knoxville, TN	47.11	61	50	33
49	Philadelphia, PA	47.10	65	21	72
50	Charleston, SC	46.31	26	91	34
51	New Haven, CT	46.16	79	18	68
52	Phoenix, AZ	45.72	59	72	39
53	San Antonio, TX	45.54	53	48	63
54	Syracuse, NY	45.50	47	62	3
55	Colorado Springs, CO	45.04	33	90	49
56	Milwaukee, WI	44.72	66	61	54
57	Grand Rapids, MI	44.50	46	75	45
58	El Paso, TX	44.50	71	67	41
59	Kansas City, MO	44.20	38	95	44
60	Allentown, PA	43.76	82	28	48
61	Charlotte, NC	43.64	28	69	74
62	Oklahoma City, OK	43.56	60	93	38
63	Virginia Beach, VA	42.93	52	71	66
64	Honolulu, HI	42.58	74	94	31
65	Jacksonville, FL	41.87	57	52	78
66	Miami, FL	41.71	41	53	82
67	Indianapolis, IN	41.53	37	46	90
68	Akron, OH	41.26	69	64	65
69	Bakersfield, CA	41.05	90	44	69
70	Ogden, UT	40.89	44	73	50
71	Provo, UT	40.85	50	70	43
72	Augusta, GA	40.54	36	83	76
73	Tulsa, OK	40.48	77	98	32
74	Las Vegas, NV	40.34	72	96	47
75	Riverside, CA	39.88	99	16	88
76	Birmingham, AL	39.69	43	92	73
77	Wichita, KS	38.36	85	51	81
78	Youngstown, OH	38.11	97	60	2
79	Palm Bay, FL	38.02	31	99	37
80	Toledo, OH	37.90	86	63	77
81	Louisville, KY	37.73	84	88	64
82	Scranton, PA	37.73	89	68	8
83	Detroit, MI	37.66	63	78	84
84	Baton Rouge, LA	37.29	67	81	83
85	Chattanooga, TN	37.21	70	80	75
86	New Orleans, LA	36.67	95	89	59
87	Bridgeport, CT	36.49	75	47	93
88	Lakeland, FL	36.16	87	58	58
89	Fresno, CA	35.74	93	42	92
90	Stockton, CA	35.51	100	38	89
91	Oxnard, CA	35.08	88	34	99
92	Greensboro, NC	34.91	80	65	91
93	Winston-Salem, NC	34.90	81	77	86
94	McAllen, TX	34.45	94	79	19
95	Deltona, FL	34.08	92	49	94
96	Little Rock, AR	29.43	73	97	95
97	Memphis, TN	29.27	83	84	97
98	North Port, FL	28.01	91	82	100
99	Jackson, MS	27.55	78	100	96
100	Cape Coral, FL	26.49	96	86	98

* Metro Area refers to a Metropolitan Statistical Area (MSA). Except for “Total Score,” all columns show relative ranks, where 1 indicates the best conditions in that category.

The study presents a comparative snapshot of STEM job markets. To provide additional context, WalletHub analyst Chip Lupo responded to follow-up questions from DIW.

Q: What's the #1 mistake STEM professionals make when evaluating metros - and what critical factors do they typically overlook?

The biggest mistakes STEM professionals make when evaluating metro areas are zeroing in on a specific salary threshold and chasing a city’s tech reputation. High pay doesn’t always translate into better outcomes if housing is expensive, wage growth is slow, or job options are limited. 

People also tend to overlook what really drives long-term opportunity, like how many STEM jobs are available, how fast the sector is growing, and whether wages keep up with the cost of living. Just as important are factors such as R&D investment, strong engineering schools, and an active innovation ecosystem. 

With many STEM jobs allowing remote work, the smartest move often isn’t choosing the flashiest tech hub, but finding a place that balances opportunity, affordability, and quality of life.

Q: Your expert commentary mentioned AI weakening entry-level STEM hiring. Which specific metros or STEM fields are most/least affected by this shift, and how should recent grads adjust their strategies?

STEM jobs are still in high demand and pay well, but AI is changing the entry-level landscape by automating routine tasks, making some junior roles less plentiful. Graduates should focus on areas with high job growth and plenty of STEM openings, like Boston, Seattle, and Atlanta, while upskilling to take on tasks that are harder to automate. Smaller markets like North Port, FL and McAllen, TX offer fewer opportunities, so location and adaptability are key for early-career success.

Q: Federal defunding of basic science research was flagged as a major concern. Beyond research roles, how might this impact STEM professionals in digital tech, software engineering, and other private sector fields? Should they factor this into their metro decisions?

Federal research funding fuels innovation that private-sector STEM jobs rely on. Cuts or shifts in R&D could slow new tech development, limit collaboration with schools and labs, and affect high-tech job growth. Metros with strong R&D funding and innovation tend to have more STEM jobs, higher pay, and better long-term growth opportunities. Even if a job can be done remotely, being near these innovation hubs can make a real difference in career prospects. That said, it’s difficult to predict which areas will get the most funding years into the future. 

Q: For Gen Z STEM grads entering the market in 2026-2027, would you recommend a different top 5 metros than for experienced professionals? What changes based on career stage?

Gen Z STEM grads entering the job market should weigh entry-level opportunities more heavily than experienced professionals. While big cities such as Boston, Seattle, Austin, Atlanta, and Pittsburgh rank highly overall, new grads may benefit from areas with more job openings per capita and high starting pay. For example, Greenville, SC has the most per-capita STEM job openings (18.4 times more than North Port, FL), and San Jose, CA offers the highest average monthly earnings for new STEM employees (nearly four times higher than Lakeland, FL). Atlanta also ranks in the top 10 for median STEM earnings adjusted for the cost of living, at more than $110,000.

Career stage matters because early-career STEM workers prioritize getting their foot in the door, along with a strong starting salary and growth potential, whereas experienced professionals can weigh factors like STEM density, R&D intensity, quality-of-life rankings, and executive pay. For new grads, focusing on metro areas that maximize early opportunity can help launch a career even if overall rankings differ slightly.

Q: Looking at your 2026 data trends, which metros show the strongest momentum for growth - and what skills should STEM professionals prioritize to position themselves in these emerging markets?

Boston, Atlanta, Seattle, Pittsburgh, and Austin show the strongest momentum for STEM growth. They combine abundant job openings, high wages, strong STEM education, and active innovation ecosystems. 

With STEM roles making up a large share of employment and salaries well above the national median, targeting these metro areas can boost career growth and earning potential while also offering quality-of-life advantages

Note: AI tools assisted with drafting and polishing this post. All content was human-reviewed and approved.

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by Asim BN via Digital Information World

ChatGPT Health promises to personalise health information. It comes with many risks

Julie Ayre, University of Sydney; Adam Dunn, University of Sydney, and Kirsten McCaffery, University of Sydney

Image: Berke Citak / Unsplash

Many of us already use generative artificial intelligence (AI) tools such as ChatGPT for health advice. They give quick, confident and personalised answers, and the experience can feel more private than speaking to a human.

Now, several AI companies have unveiled dedicated “health and wellness” tools. The most prominent is ChatGPT Health, launched by OpenAI earlier this month.

ChatGPT Health promises to generate more personalised answers, by allowing users to link medical records and wellness apps, upload diagnostic imaging and interpret test results.

But how does it really work? And is it safe?

Most of what we know about this new tool comes from the company that launched it, and questions remain about how ChatGPT Health would work in Australia. Currently, users in Australia can sign up for a waitlist to request access.

Let’s take a look.

AI health advice is booming

Data from 2024 shows 46% of Australians had recently used an AI tool.

Health queries are popular. According to OpenAI, one in four regular ChatGPT users worldwide submit a health-related prompt each week.

Our 2024 study estimated almost one in ten Australians had asked ChatGPT a health query in the previous six months.

This was more common for groups that face challenges finding accessible health information, including:

• people born in a non-English speaking country
• those who spoke another language at home
• people with limited health literacy.

Among those who hadn’t recently used ChatGPT for health, 39% were considering using it soon.

How accurate is the advice?

Independent research consistently shows generative AI tools do sometimes give unsafe health advice, even when they have access to a medical record.

There are several high-profile examples of AI tools giving unsafe health advice, including when ChatGPT allegedly encouraged suicidal thoughts.

Recently, Google removed several AI Overviews on health topics – summaries which appear at the top of search results – after a Guardian investigation found the advice about blood tests results was dangerous and misleading.

This was just one health prompt they studied. There could be much more advice the AI is getting wrong we don’t know about yet.

So, what’s new about ChatGPT Health?

The AI tool has several new features aimed to personalise its answers.

According to OpenAI, users will be able to connect their ChatGPT Health account with medical records and smartphone apps such as MyFitnessPal. This would allow the tool to use personal data about diagnoses, blood tests, and monitoring, as well as relevant context from the user’s general ChatGPT conversations.

OpenAI emphasises information doesn’t flow the other way: conversations in ChatGPT Health are kept separate from general ChatGPT, with stronger security and privacy. The company also says ChatGPT Health data won’t be used to train foundation models.

OpenAI says it has worked with more than 260 clinicians in 60 countries (including Australia), to give feedback on and improve the quality of ChatGPT Health outputs.

In theory, all of this means ChatGPT Health could give more personalised answers compared to general ChatGPT, with greater privacy.

But are there still risks?

Yes. OpenAI openly states ChatGPT Health is not designed to replace medical care and is not intended for diagnosis or treatment.

It can still make mistakes. Even if ChatGPT Health has access to your health data, there is very little information about how accurate and safe the tool is, and how well it has summarised the sources it has used.

The tool has not been independently tested. It’s also unclear whether ChatGPT Health would be considered a medical device and regulated as one in Australia.

The tool’s responses may not reflect Australian clinical guidelines, our health systems and services, and may not meet the needs of our priority populations. These include First Nations people, those from culturally and linguistically diverse backgrounds, people with disability and chronic conditions, and older adults.

We don’t know yet if ChatGPT Health will meet data privacy and security standards we typically expect for medical records in Australia.

Currently, many Australians’ medical records are incomplete due to patchy uptake of MyHealthRecord, meaning even if you upload your medical record, the AI may not have the full picture of your medical history.

For now, OpenAI says medical record and some app integrations are only available in the United States.

So, what’s the best way to use ChatGPT for health questions?

In our research, we have worked with community members to create short educational materials that help people think about the risks that come with relying on AI for health advice, and to consider other options.

Higher risk

Health questions that would usually require clinical expertise to answer carry more risk of serious consequences. This could include:

• finding out what symptoms mean
• asking for advice about treatment
• interpreting test results.

AI responses can often seem sensible – and increasingly personalised – but that doesn’t necessarily mean they are correct or safe. So, for these higher-risk questions, the best option is always to speak with a health professional.

Lower risk

Other health questions are less risky. These tend to be more general, such as:

• learning about a health condition or treatment option
• understanding medical terms
• brainstorming what questions to ask during a medical appointment.

Ideally, AI is just one of the information sources you use.

Where else can I get free advice?

In Australia we have a free 24/7 national phone service, where anyone can speak with a registered nurse about their symptoms: 1800 MEDICARE (1800 633 422).

Symptom Checker, operated by healthdirect, is another publicly funded, evidence-based tool that will help you understand your next steps and connect you with local services.

AI tools are here to stay

For now, we need clear, reliable, independent, and publicly available information about how well the current tools work and the limits of what they can do. This information must be kept up-to-date as the tools evolve.

Purpose-built AI health tools could transform how people gain knowledge, skills and confidence to manage their health. But these need to be designed with communities and clinicians, and prioritise accuracy, equity and transparency.

It is also essential to equip our diverse communities with the knowledge and skills to navigate this new technology safely.

Julie Ayre, Post Doctoral Research Fellow, Sydney Health Literacy Lab, University of Sydney; Adam Dunn, Professor of Biomedical Informatics, University of Sydney, and Kirsten McCaffery, NHMRC Principal Research Fellow, Sydney School of Health, University of Sydney

This article is republished from The Conversation under a Creative Commons license. Read the original article.

by External Contributor via Digital Information World

Most Americans Don’t Know About Web Hosting, But Know They Want It Cheap

Written by Derick Migliacci. Edited by Asim BN. Reviewed by Ayaz Khan.

Web hosting knowledge in America

Web hosting is one of the most important aspects of websites on the internet. All sites need a hosting provider to keep their pages running and users online. Web hosting is currently supporting billions of websites and is also a multi-billion dollar industry with exponential growth in the future.

As a foundational piece of the internet, you would assume that a majority of internet-dependent Americans would know a lot about this concept. But according to cybersecurity website, All About Cookies, that may not be the case.

A 2025 All About Cookies survey found that only 40% of Americans have a general idea of the concept, while 24% reported they don't know the meaning of web hosting.

Additionally, the All About Cookies survey found that around one-fourth (25%) of respondents couldn’t correctly identify the essential functions and tasks of what a web host does. While most correctly identified that a web host stores website files and data, manages domain names, and makes a website visible to online users, some confuse web hosting responsibilities with tasks that align more with web design.

As evidenced by the graphic above, 27% of respondents incorrectly believed that web hosting consists of design elements, which is typically handled by a dedicated web or UX designer. Other users incorrectly believed cybersecurity measures like protecting sites from viruses or installing antiviruses as tasks a web host would handle. Alongside the incorrect answers, 6% of survey participants admitted they were not fully sure about what web hosting entailed.

Price is the #1 factor for people when considering a web host

Many individuals build websites for personal brands, their own interests, or a variety of other reasons and require a host to get these websites live.

Survey respondents put affordability at the forefront of their minds when making web hosting decisions, as evidenced by the graphic below.

Ease of setup was the second most important prioritization at 46%, followed by security and backups (39%).

Nearly one-third of Americans have tried building a website

With affordability and ease of setup at the top of user’s lists, it’s no surprise that many turn to popular web building providers such as Squarespace or Wix. These sites provide users with ease of setup without having to spend the money or resources to outsource the project. According to the All About Cookies survey, 74% of respondents who tried building a website on their own relied on these tools.

With the combination of ease of use and heavy marketing tactics, web builders are at the top of the list when getting their site up and running. With that ease of use and affordability, these users are trading the full scale controllability that web hosting would provide them for a cheaper and more simplistic avenue than web hosting would.

Control over web hosting versus website builders is understood by only 40% of respondents with general web hosting knowledge. According to data pulled from the All About Cookies survey, 32% of Americans have actually tried building a website at some point in time by attempting to code it from scratch.

Web Building For Small Businesses

Web building is a huge part of helping to build a small business, with the current age of online shopping and digital marketing it’s almost impossible to not employ someone or attempt to host a website yourself for your business.

With many small businesses having limited funds when starting out, a majority build and manage their own site in-house. 65% of small business owners don’t outsource their websites and opt to build one themselves due to factors such as lack of funds or resources.

When it comes to how much small business owners pay for web building, they’re willing to spend $250 annually, on average. Of the small business owners surveyed, 68% reported spending between $50 and $250 annually.

Final Thoughts

Web hosting and building is something that users need in today’s digital age, and these findings prove that small business owners and individuals alike recognize that. The disconnect comes with people’s lack of education on the topic, but their desire to host and build with affordability as their main priority regardless of the reason for why they want to host or build their site.

Having a full knowledge of the web hosting and building landscape could benefit small business owners as well as individuals regardless of if users choose to build/host/code or employ someone to do so. Users who can combine their knowledge of web hosting with their wants and needs can make more informed web hosting decisions that could prove to give them a leg up from their less experienced peers.

About author:
Derick Migliacci is a Digital PR Strategist for AllAboutCookies.org. He brings 3 years of experience in the PR world as well as a passion for digital trends, cybersecurity, and technology.

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• Gen Z Financial Struggles: 72% Social Life Impact, 67% Mental Health Hit, 47% Have One Hour or Less Free Daily

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by Guest Contributor via Digital Information World

Gen Z Financial Struggles: 72% Social Life Impact, 67% Mental Health Hit, 47% Have One Hour or Less Free Daily

Edited by Asim BN

Financial challenges have a wide-reaching impact, and in a recent study, Gen Z reported their social lives (72%), mental health (67%) and physical health (62%) have suffered due to money constraints in the last year.

Image: Karolina Grabowska kaboompics.com / pexels

The survey of 2,000 Gen Z hourly workers also found that more than a third (36%) are working multiple jobs, and just about half (47%) have an hour or less of free time each day.

Despite their grind, more than two-thirds of Gen Z workers (68%) doubt they’ll ever be able to fully retire.

And those who are confident they’ll be able to retire are working two jobs, on average, while those who are uncertain about retiring work just one.

This poses the question: Will Gen Z actually need to work two jobs to have enough money to retire?

The survey was conducted by Talker Research on behalf of DailyPay to investigate Gen Z’s financial health and the ways money difficulties have impacted their overall well-being, work and retirement plans.

According to the findings, most Gen Z (77%) think they’ll need to work past the typical retirement age to make ends meet: Half (49%) believe they’ll need to work full-time, and 29% anticipate they’ll need to work at least part-time.

And while, holistically, 67% of Gen Z hourly workers are still proactively saving for retirement, only a small group of those who don’t think they’ll retire are still saving for it just in case (44%), putting this significant group of people in a precarious financial position.

Looking at respondents’ work/life balance, the majority of Gen Z respondents (56%) went so far as to say they don’t feel like they have lives outside of their jobs.

Respondents also said they eat mostly home-cooked meals (44%), shop at discount stores (38%), opt to do free activities for fun (36%) and even cut their own hair (26%) to limit their spending.

Interestingly, Gen Z also reported that they’re financially responsible for one other person, on average, along with themselves.

Considering this, some of their more intense money-saving habits make a bit more sense in context. These include keeping the thermostat very low in the winter and high in the summer (18%), taking short or cold showers (15%) and air-drying their clothes instead of using a dryer (13%).

2025 was an incredibly difficult financial year for many, if not most, and when Gen Zers were asked about the most extreme things they did in the last year to save money, the responses put things into perspective.

Some respondents said they cut back on showering to reduce their water bills, while others turned off their hot water or electricity, did laundry in the bathtub and stopped buying necessities like groceries and toilet paper.

“Gen Z is facing a financial crisis that is actively undermining their health, their work performance and their hope for retirement,” said Andrew Brandman, chief operating officer at DailyPay. “The outdated pay cycle is misaligned with the younger generation’s modern financial needs and, for many, is negatively impacting their stability and well-being.”

In the study, the majority of Gen Z hourly workers (63%) reported their work performance has taken a hit in the last year because of their money worries.

More than a third (35%) also admitted they accepted their current jobs because they were desperate for work and many (31%) ended up in their current positions because they were attracted to how frequently they’d be paid (e.g. daily, weekly), instead of an attraction to the role itself.

“On-Demand Pay is no longer a niche perk; for many, it’s an essential benefit that restores control over pay and provides financial security to the employee,” said Brandman. “Empowering workers with real-time access to the pay they’ve already earned can be one of the most effective ways to help Gen Z stabilize their finances and thrive.”

GEN Z’S TOP MONEY SAVING HACKS

• Eating mostly home-cooked meals (44%)
• Shopping at discount stores (38%)
• Using coupon apps, cashback sites and waiting for sales (36%)
• Doing free activities for fun (36%)
• Meal prepping (31%)
• Buying in bulk (30%)
• Cutting my own hair (26%)
• Buying secondhand things (25%)
• Buying generic brands only (24%)
• DIY home repairs (21%)
• DIY car maintenance (19%)
• Keeping the thermostat very low in the cold months and higher during the warm months (18%)
• Using public transit (17%)
• Carpooling with others when possible (16%)
• Biking or walking instead of driving (15%)
• Taking shorter or cold showers (15%)
• Air-drying clothes instead of using a dryer (13%)

Note: This article was originally published on TalkerResearch and republishing here as per their guidelines.

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by External Contributor via Digital Information World

Feeling unprepared for the AI boom? You’re not alone

Patrick Barry, University of Michigan

Image: DIW-Aigen

Journalist Ira Glass, who hosts the NPR show “This American Life,” is not a computer scientist. He doesn’t work at Google, Apple or Nvidia. But he does have a great ear for useful phrases, and in 2024 he organized an entire episode around one that might resonate with anyone who feels blindsided by the pace of AI development: “Unprepared for what has already happened.”

Coined by science journalist Alex Steffen, the phrase captures the unsettling feeling that “the experience and expertise you’ve built up” may now be obsolete – or, at least, a lot less valuable than it once was.

Whenever I lead workshops in law firms, government agencies or nonprofit organizations, I hear that same concern. Highly educated, accomplished professionals worry whether there will be a place for them in an economy where generative AI can quickly – and relativity cheaply – complete a growing list of tasks that an extremely large number of people currently get paid to do.

Seeing a future that doesn’t include you

In technology reporter Cade Metz’s 2022 book, “Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World,” he describes the panic that washed over a veteran researcher at Microsoft named Chris Brockett when Brockett first encountered an artificial intelligence program that could essentially perform everything he’d spent decades learning how to master.

Overcome by the thought that a piece of software had now made his entire skill set and knowledge base irrelevant, Brockett was actually rushed to the hospital because he thought he was having a heart attack.

“My 52-year-old body had one of those moments when I saw a future where I wasn’t involved,” he later told Metz.

In his 2018 book, “Life 3.0: Being Human in the Age of Artificial Intelligence,” MIT physicist Max Tegmark expresses a similar anxiety.

“As technology keeps improving, will the rise of AI eventually eclipse those abilities that provide my current sense of self-worth and value on the job market?”

The answer to that question, unnervingly, can often feel outside of our individual control.

“We’re seeing more AI-related products and advancements in a single day than we saw in a single year a decade ago,” a Silicon Valley product manager told a reporter for Vanity Fair back in 2023. Things have only accelerated since then.

Even Dario Amodei – the co-founder and CEO of Anthropic, the company that created the popular chatbot Claude – has been shaken by the increasing power of AI tools. “I think of all the times when I wrote code,” he said in an interview on the tech podcast “Hard Fork.” “It’s like a part of my identity that I’m good at this. And then I’m like, oh, my god, there’s going to be these (AI) systems that [can perform a lot better than I can].”

The irony that these fears live inside the brain of someone who leads one of the most important AI companies in the world is not lost on Amodei.

“Even as the one who’s building these systems,” he added, “even as one of the ones who benefits most from (them), there’s still something a bit threatening about (them).”

Autor and agency

Yet as the labor economist David Autor has argued, we all have more agency over the future than we might think.

In 2024, Autor was interviewed by Bloomberg News soon after publishing a research paper titled Applying AI to Rebuild Middle-Class Jobs. The paper explores the idea that AI, if managed well, might be able to help a larger set of people perform the kind of higher-value – and higher-paying – “decision-making tasks currently arrogated to elite experts like doctors, lawyers, coders and educators.”

This shift, Autor suggests, “would improve the quality of jobs for workers without college degrees, moderate earnings inequality, and – akin to what the Industrial Revolution did for consumer goods – lower the cost of key services such as healthcare, education and legal expertise.”

It’s an interesting, hopeful argument, and Autor, who has spent decades studying the effects of automation and computerization on the workforce, has the intellectual heft to explain it without coming across as Pollyannish.

But what I found most heartening about the interview was Autor’s response to a question about a type of “AI doomerism” that believes that widespread economic displacement is inevitable and there’s nothing we can do to stop it.

“The future should not be treated as a forecasting or prediction exercise,” he said. “It should be treated as a design problem – because the future is not (something) where we just wait and see what happens. … We have enormous control over the future in which we live, and [the quality of that future] depends on the investments and structures that we create today.”

At the starting line

I try to emphasize Autor’s point about the future being more of a “design problem” than a “prediction exercise” in all the AI courses and workshops I teach to law students and lawyers, many of whom fret over their own job prospects.

The nice thing about the current AI moment, I tell them, is that there is still time for deliberate action. Although the first scientific paper on neural networks was published all the way back in 1943, we’re still very much in the early stages of so-called “generative AI.”

No student or employee is hopelessly behind. Nor is anyone commandingly ahead.

Instead, each of us is in an enviable spot: right at the starting line.

Patrick Barry, Clinical Assistant Professor of Law and Director of Digital Academic Initiatives, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read next: AI-Assisted Coding Reaches 29% of New US Software Code

by External Contributor via Digital Information World

AI-Assisted Coding Reaches 29% of New US Software Code

Edited by Asim BN. Reviewed by Ayaz Khan

Generative AI is reshaping software development – and fast. A new study published in Science shows that AI-assisted coding is spreading rapidly, though unevenly: in the U.S., the share of new code relying on AI rose from 5% in 2022 to 29% in early 2025, compared with just 12% in China. AI usage is highest among less experienced programmers, but productivity gains go to seasoned developers.

The Study In A Nutshell

• AI-assisted coding is spreading rapidly: In the U.S., the share of AI-generated code rose from 5% in 2022 to nearly 30% by the end of 2024
• Large regional gaps: Adoption was highest in the U.S. (29%), followed by Germany (23%), France (24%) and India (20%); China (12%) and Russia (15%) lag behind (as of early 2025)
• Measured productivity gains: In the aggregate, generative AI increased programmers’ productivity by an estimated of 3.6%
• Substantial economic impact: AI-assisted coding adds at least $23 billion per year to the U.S. economy
• Unequal effects: Less experienced programmers use AI more often, but productivity gains accrue almost exclusively to experienced developers

The software industry is enormous. In the U.S. economy alone, firms spend an estimated $600 billion a year in wages on coding-related work. Every day, billions of lines of code keep the global economy running. How is AI changing this backbone of modern life?

In a study published in Science, a research team led by the Complexity Science Hub (CSH) found that by the end of 2024, around one-third of all newly written software functions – self-contained subroutines in a computer program – in the United States were already being created with the support of AI systems.

“We analyzed more than 30 million Python contributions from roughly 160,000 developers on GitHub, the world’s largest collaborative programming platform,” says Simone Daniotti of CSH and Utrecht University. GitHub records every step of coding – additions, edits, improvements – allowing researchers to track programming work across the globe in real time. Python is one of the most widely used programming languages in the world.

Regional Gaps Are Large

The team used a specially trained AI model to identify whether blocks of code were AI-generated, for instance via ChatGPT or GitHub Copilot.

“The results show extremely rapid diffusion,” explains Frank Neffke, who leads the Transforming Economies group at CSH. “In the U.S., AI-assisted coding jumped from around 5% in 2022 to nearly 30% in the last quarter of 2024.”

At the same time, the study found wide differences across countries. “While the share of AI-supported code is highest in the U.S. at 29%, Germany reaches 23% and France 24%, followed by India at 20%, which has been catching up fast,” he says, while Russia (15%) and China (12%) still lagged behind at the end of our study.

“It’s no surprise the U.S. leads – that’s where the leading LLMs come from. Users in China and Russia have faced barriers to accessing these models, blocked by their own governments or by the providers themselves, though VPN workarounds exist. Recent domestic Chinese breakthroughs like DeepSeek, released after our data ends in early 2025, suggest this gap may close quickly,” says Johannes Wachs, a faculty member at CSH and associate professor at Corvinus University of Budapest.

Global diffusion of AI-assisted coding and its impact | Left: The share of AI-written Python functions (2019-2024) grows rapidly, but countries differ in their adoption rates. The U.S. leads the early adoption of generative AI, followed by European nations such as France and Germany. From 2023 onward, India rapidly catches up, whereas adoption in China and Russia progresses more slowly. Right: Comparing usage rates for the same programmers at different points in time, generative AI adoption is associated with increased productivity (commits), breadth of functionality (library use) and exploration of new functionality (library entry), but only for senior developers, while early-career developers do not derive any statistically significant benefits from using generative AI (c) Complexity Science Hub

Experienced Developers Benefit Most

The study shows that the use of generative AI increased programmers’ productivity by 3.6% by the end of 2024. “That may sound modest, but at the scale of the global software industry it represents a sizeable gain,” says Neffke, who is also a professor at Interdisciplinary Transformation University Austria (IT:U).

The study finds no differences in AI usage between women and men. By contrast, experience levels matter: less experienced programmers use generative AI in 37% of their code, compared to just 27% for experienced programmers. Despite this, the productivity gains the study documents are driven exclusively by experienced users. “Beginners hardly benefit at all,” says Daniotti. Generative AI therefore does not automatically level the playing field; it can widen existing gaps.

In addition, experienced software developers experiment more with new libraries and unusual combinations of existing software tools. “This suggests that AI does not only accelerate routine tasks, but also speeds up learning, helping experienced programmers widen their capabilities and more easily venture into new domains of software development,” says Wachs.

Economic Gains

What does all of this mean for the economy? “The U.S. spends an estimated $637 billion to $1.06 trillion annually in wages on programming tasks, according to an analysis of about 900 different occupations,” says co-author Xiangnan Feng from CSH. If 29% of code is AI-assisted and productivity rises by 3.6%, that adds between $23 and $38 billion in value each year. “This is likely a conservative estimate,” Neffke points out, “the economic impact of generative AI in software development was already substantial at the end of 2024 and is likely to have increased further since our analysis.”

“When even a car has essentially become a software product, we need to understand the hurdles to AI adoption – at the company, regional, and national levels – as quickly as possible”. Frank Neffke - SH Faculty.

Looking Ahead

Software development is undergoing profound transformation. AI is becoming central to digital infrastructure, boosting productivity and fostering innovation – but mainly for people who already have substantial work experience.

“For businesses, policymakers, and educational institutes, the key question is not whether AI will be used, but how to make its benefits accessible without reinforcing inequalities,” says Wachs. “When even a car has essentially become a software product, we need to understand the hurdles to AI adoption – at the company, regional, and national levels – as quickly as possible,” Neffke adds.

About the study

The study “ Who is using AI to code? Global diffusion and impact of Generative AI ” by Simone Daniotti, Johannes Wachs, Xiangnan Feng, and Frank Neffke has been published in Science (doi: 10.1126/science.adz9311).

Note: This post was originally published on the Complexity Science Hub and is republished on DIW with permission. No AI was used in writing this post.

by External Contributor via Digital Information World

Lack of coordination is leaving modern slavery victims and survivors vulnerable, say experts

Written by: Joe Stafford - The University of Manchester. Reviewed by Asim BN.

Image: Nano banana

Researchers at The University of Manchester are calling for stronger, coordinated partnerships to tackle modern slavery and human trafficking, warning that gaps between organisations risk leaving victims and survivors without consistent protection and support.

Their appeal comes in a new review commissioned by Greater Manchester Combined Authority (GMCA) , which examines how organisations across the city region work together to identify, safeguard and support people affected by modern slavery and human trafficking. The review focuses on partnerships involving local authorities, statutory services, law enforcement, housing providers and voluntary and community sector organisations.

The authors argue that tackling modern slavery depends on robust, long-term collaboration rather than ad hoc arrangements. While organisations across Greater Manchester have developed innovative partnership approaches, the review finds that these are not always embedded consistently across the system. Among the review’s key recommendations, the authors are calling for:

- Clearer strategic governance to strengthen modern slavery and human trafficking partnerships at a Greater Manchester-wide level.

- More consistent roles and responsibilities across organisations, so victims/survivors do not fall through gaps between services.

- Improved information-sharing and referral pathways, ensuring concerns are acted on quickly and safely.

- Sustainable funding and resources to support partnership working, rather than reliance on short-term arrangements.

- Stronger links between safeguarding, housing, immigration advice and criminal justice responses, reflecting the needs of victims.

The review suggests that where partnerships are well established, outcomes for victims are more likely to be improved. Such embedded collaboration enables earlier identification of exploitation, better safeguarding responses and coordinated support to help individuals recover and rebuild their lives. Strong partnerships also support disruption of criminal activity by improving intelligence-sharing and joint working.

However, the authors highlight challenges which can weaken partnership arrangements including variations in local practice, capacity pressures and funding uncertainty. Frontline professionals reported that without clear structures and shared accountability, collaboration often relies on personal relationships, making it fragile and difficult to sustain.

The researchers also note that victims and survivors of modern slavery often face overlapping vulnerabilities including insecure housing, mental ill-health and immigration insecurity. Without joined-up working across sectors, these complexities can delay support and increase the risk of re-exploitation.

The authors stress that the findings have national relevance due to a relatively cohesive modern slavery partnership approach in Greater Manchester. As awareness of modern slavery grows, public bodies across the UK face pressure to demonstrate good quality partnership responses. The review positions Greater Manchester as a potential leader, but cautions that this requires investment in governance, coordination and shared learning.

“This review shows that partnership working is not optional when tackling modern slavery and human trafficking - it is essential. The needs of victims and survivors cut across organisational boundaries, and responses must do the same. Our recommendations set out how partners across Greater Manchester can strengthen their approach and provide protection and support.” - Dr Jon Davies.

This article was originally published by The University of Manchester and is republished with permission.

by External Contributor via Digital Information World