Who Tops the List of the World’s Leading Research Universities?

Universities in the United States continue to lead the 2025 global research rankings. Harvard University secured the top spot, maintaining its edge in research volume, citation impact, and academic reach. Other U.S. institutions followed closely, including MIT, Stanford, and several University of California campuses. The presence of Berkeley, San Diego, San Francisco, and Los Angeles reflects the system’s consistent output across disciplines.

Johns Hopkins, Yale, Princeton, and Columbia also stayed in strong positions, backed by broad academic programs and long-standing research funding. Their place in the rankings reflects a steady rhythm of publication and collaboration, rather than sudden shifts.

UK and European Universities Hold Ground

Universities in the United Kingdom performed steadily, though fewer in number. Oxford and Cambridge remained in the top five. Both have sustained their global visibility through consistent publication impact and subject diversity. Imperial College London and King’s College London also kept their places, supported by research links across Europe and beyond.

• Also read: Which Jobs Face the Highest Risk of Automation, and Which Ones Are Likely Safe?

Elsewhere in Europe, ETH Zurich led among continental institutions. It stood out as the only non-English speaking university within the top ten. Amsterdam’s leading public university also made a visible mark. Outside these names, European entries were fewer, but those that did rank high tended to do so on strength in specialized fields.

Asia’s Academic Climb Gains Pace

Asian universities continued to climb. China’s Tsinghua and Peking University made strong appearances. Their rise has been tied to growth in research investment and international attention. Singapore’s National University and Nanyang Technological University remained competitive, backed by stable funding and strategic partnerships.

South Korea and Japan also saw moderate representation, although their institutions ranked slightly lower this year. The general trend across Asia suggests a slow but steady push toward stronger international placement.

Oceania and Canada Keep Steady Output

Australian universities held a familiar pattern. Melbourne and Sydney ranked highest within the region. Both showed strength in medicine, engineering, and environmental science. The University of Queensland and the University of New South Wales followed, with outputs that held steady across research categories.

Canada’s University of Toronto remained its highest-ranked institution. It scored well across publication metrics, reputation, and collaboration. McGill and British Columbia continued to perform solidly, especially in life sciences and social policy areas.

Methodology Focused on Research Activity

The 2025 rankings, by USNews, reviewed over 2,200 institutions across 105 countries. They relied on thirteen indicators related to research, including publication volume, citation strength, and the share of internationally co-authored papers. Results also considered how often a university’s work appeared among the top ten percent of global studies by citation count.

Teaching quality, employment outcomes, and student satisfaction were not included in this year’s evaluation. The rankings concentrated solely on research performance, providing a clearer lens into academic influence across borders.

Rank	University (Country)	Global Score
1	Harvard University (U.S.)	100
2	Massachusetts Institute of Technology (U.S.)	97.2
3	Stanford University (U.S.)	94.5
4	University of Oxford (UK)	88.3
5	University of Cambridge (UK)	86.8
6	University of California Berkeley (U.S.)	86.4
7	University College London (UK)	86.2
8	University of Washington Seattle (U.S.)	86.1
9	Yale University (U.S.)	86
10	Columbia University (U.S.)	85.8
11	Imperial College London (UK)	85.2
11	Tsinghua University (China)	85.2
13	University of California Los Angeles (U.S.)	84.9
14	John Hopkins University (U.S.)	84.4
15	University of Pennsylvania (U.S.)	84
16	Cornell University (U.S.)	83.6
16	Princeton University (U.S.)	83.6
16	University of California San Francisco (U.S.)	83.6
16	University of Toronto (Canada)	83.6
20	National University of Singapore (Singapore)	20
21	University of California San Diego (U.S.)	83.2
21	University of Michigan (U.S.)	83.2
23	California Institute of Technology (U.S.)	82.9
24	Northwestern University (U.S.)	81.5
25	Peking University (China)	81.1
26	University of Chicago (U.S.)	81
27	Duke University (U.S.)	80.7
28	Nanyang Technological University (China)	80.6
29	University of Sydney (Australia)	79.9
30	University of Melbourne (Australia)	79.8
31	Washington University (WUSTL) (U.S.)	79.6
32	New York University (U.S.)	79.2
33	University of Amsterdam (Netherlands)	79.1
34	University of New South Wales Sydney (Australia)	79
35	ETH Zurich (Switzerland)	78.9
36	King's College London (UK)	78.7
37	Chinese University of Hong Kong (Hong Kong)	78.5
38	Monash University (Australia)	78.4
39	University of Edinburgh (UK)	78.2
40	Icahn School of Medicine at Mount Sinai (U.S.)	77.5

A Gradual Shift, Not a Shake-Up

Although the top positions saw few changes, movement lower in the list pointed to broader shifts. Several institutions from Asia and smaller European countries inched upward. While the overall picture still tilts toward the English-speaking world, others are beginning to close the gap, gradually but persistently.

Notes: This post was edited/created using GenAI tools.

Read next: The Best and Worst U.S. States for Data Privacy in 2025

by Irfan Ahmad via Digital Information World

OpenAI’s Math Model Hits Gold-Level Score at Global Olympiad

OpenAI’s newest experimental model has crossed an unexpected milestone. At this year’s International Math Olympiad (IMO), the system solved five out of six problems, earning a gold-level score typically reserved for elite young mathematicians. It reached 35 out of 42 possible points, placing it within the top 10 percent of over 600 contestants worldwide.

The Olympiad, first held in Romania in 1959, is considered one of the toughest math competitions. Students face two exams over two days, each lasting four and a half hours and containing three problems. These questions aren’t just about solving equations, they demand abstract reasoning, creative problem-solving, and a strong grasp of advanced algebra and pre-calculus.

AI models have been tested on math before, but usually in lower-stakes settings. Just last year, researchers were using basic arithmetic and high school problems to measure model capability. This performance suggests the bar is now higher.

Performance Under Human Conditions

OpenAI’s model tackled the same problems as the human contestants, under the same time constraints. According to researchers involved, it showed an unusual ability to focus for long stretches and craft detailed, structured solutions, something that hasn't been easy for previous language models.

Unlike DeepMind’s AlphaGeometry, which was built specifically for math, OpenAI’s system is a general-purpose language model. That makes this result more surprising. The model wasn’t tuned to master Olympiad-style problems; instead, it drew on broader training and still kept up.

• Also read: Can AI Argue Better Than You? New Study Suggests It Might

Team members described it as capable of sustained reasoning, working through problems with a level of endurance and logic that pushed past previous benchmarks. According to internal commentary, the model didn’t just recall formulas or mimic surface-level patterns. It built full mathematical arguments, step by step.

Predictions That Didn't Hold

The result also turned a few expert predictions on their head. Just weeks before the competition, mathematician Terence Tao suggested that AI models might struggle to reach Olympiad standards. On a podcast appearance, he pointed to simpler contests as more realistic short-term targets.

Similar doubts had come from other corners of the tech world. In 2024, investor Peter Thiel speculated that models wouldn’t be able to solve problems at this level for at least three more years. That forecast didn’t age well.

Still, even with this breakthrough, OpenAI is not rushing to deploy the model publicly. CEO Sam Altman stated that this version won’t be released anytime soon. While upcoming systems like GPT-5 are expected to improve on current capabilities, they won’t feature this level of mathematical reasoning, at least not yet.

Reactions from Across the Field

The response has been mixed. AI researcher Alexander Wei, who helped lead the work, described the success as a major step toward more general reasoning skills in AI. But not everyone is ready to call it a turning point.

Gary Marcus, a long-time critic of AI overhype, acknowledged the performance as impressive. At the same time, he raised questions about how the model was trained, whether the IMO organizers would confirm the results, and what real-world value such systems might bring. He also asked how much it cost to reach this level of performance, and whether that kind of investment could scale.

As of now, the Olympiad’s organizers have not independently verified the model’s results. That leaves some room for scrutiny. But even without formal confirmation, the development signals how fast things are moving. A year ago, the idea of an LLM competing at this level seemed far off. Now, it’s suddenly on the scoreboard.

Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.

Read next:

• The Best and Worst U.S. States for Data Privacy in 2025

• Which Jobs Face the Highest Risk of Automation, and Which Ones Are Likely Safe?
by Irfan Ahmad via Digital Information World

The Best and Worst U.S. States for Data Privacy in 2025

Montana surges into the Top 3. Michigan tumbles 28 spots. And Alaska ranks dead last. Again.

Just six months after the last edition, the 2025 Data Security Index reveals dramatic shifts in how U.S. states protect (or fail to protect) their residents’ personal data.

This report ranks states by how safe your personal information is, using real-world metrics that impact millions:

• Cybercrime per capita: How often residents fall victim to digital crimes like identity theft and online fraud
• Data breaches per capita: How frequently personal data is leaked, stolen, or exposed through hacks or mishandled records
• Data privacy laws: Whether a state has passed meaningful protections for how your data is collected, stored, and shared

These factors are compiled into a Data Safety Score out of 100, which determines each state’s position.

And this year, the changes are anything but subtle.

Key Findings

• Kentucky defends its title as the #1 safest state for your data, with the lowest cybercrime rate and strong laws.
• Montana jumped from #9 to #2, after cutting its breach rate by more than half.
• Maine fell from #43 to #49, now with the highest data breach rate in the country (1.07 per 100K residents).
• Alaska now ranks dead last (#50), with the highest cybercrime rate (914.7 per 100K).
• Only 16 states score a full 6/6 for privacy laws. Nearly 20 states still have virtually no legal protections (1/6).

Top 10 States for Data Privacy in 2025

Where you’re safest online — and how these states earned their spot.

Rank (2025)	State	Score	Rank (2024)	Change
1	Kentucky	98.20	1	Same
2	Montana	97.26	9	▲ 7
3	Tennessee	97.04	3	Same
4	New Jersey	96.72	13	▲ 9
5	Utah	96.54	7	▲ 2
6	Iowa	96.48	4	▼ 2
7	Texas	96.47	10	▲ 3
8	Minnesota	96.18	11	▲ 3
9	Virginia	95.52	5	▼ 4
10	Connecticut	95.31	19	▲ 9

1. Kentucky

2024 Rank: 1 → 2025 Rank: 1 (Same)

Kentucky defends its crown for the second year straight, and it’s no fluke. The Bluegrass State has the lowest cybercrime rate in the country (134.4 per 100K residents), barely any reported data breaches (just 0.07 per 100K), and a perfect 6 out of 6 privacy law score. It's the rare case of a state doing everything right — from enforcement to legislation — making it the safest place in America for your personal data.

2. Montana

2024 Rank: 9 → 2025 Rank: 2 (▲7)

Montana made a massive leap into the top 3 this year. What changed? It slashed its breach rate from 0.35 down to just 0.09 per 100K, one of the lowest in the U.S. And with a strong privacy law score of 6, this frontier state is proving that you don’t need to be coastal or high-tech to lead on data protection. A huge turnaround — and a wake-up call for other rural states.

3. Tennessee

2024 Rank: 3 → 2025 Rank: 3 (Same)

Tennessee holds firm in third place by staying the course. The state cut its breach rate nearly in half — from 0.20 to 0.11 — while keeping a 6/6 privacy law score. Cybercrime rose a bit to 157.9, but remains well below the national average. All in all, a strong year for digital safety in the Volunteer State.

4. New Jersey

2024 Rank: 13 → 2025 Rank: 4 (▲9)

New Jersey was one of the year's biggest climbers. Last year, its high breach rate (0.43) kept it out of the top 10. This year, that number fell to just 0.12 — a major improvement. Combine that with a solid cybercrime rate (165.3) and full legal protections, and you get a state that made privacy a priority — and saw real results.

5. Utah

2024 Rank: 7 → 2025 Rank: 5 (▲2)

Utah climbed two spots thanks to stable data practices. It kept its breach rate impressively low at 0.09, while maintaining a strong privacy law score of 6. Cybercrime did rise to 196.3 per 100K, but Utah still compares favorably with other tech-driven states. The result: a quietly powerful performance.

6. Iowa

2024 Rank: 4 → 2025 Rank: 6 (▼2)

Iowa actually improved in one key area — its breach rate dropped to 0.06 per 100K, the lowest in the country. So why the slip? A rise in cybercrime reports to 221.9 pulled its overall score down slightly. Still, with strong laws and the best breach control in the U.S., Iowa remains a digital safety leader.

• Also read: Workplace Priorities Are Shifting: Here’s What Skills Matter in 2025

7. Texas

2024 Rank: 10 → 2025 Rank: 7 (▲3)

Texas made measurable gains by cutting its breach rate from 0.26 last year to just 0.09 — a notable improvement for a state of 30 million people. While cybercrime sits at 199.3 per 100K, Texas maintains a full legal framework (6/6), keeping it competitive with other large states like California and Florida.

8. Minnesota

2024 Rank: 11 → 2025 Rank: 8 (▲3)

Minnesota quietly worked its way into the top 10 by keeping things stable and secure. With a cybercrime rate of 159.9 and a breach rate of 0.16, it sits right in the “low risk” zone — and backs it up with a perfect 6/6 privacy law score. It’s not flashy, but it’s effective.

9. Virginia

2024 Rank: 5 → 2025 Rank: 9 (▼4)

Virginia slid four spots this year. The main issue? A steady breach rate (0.15) and rising cybercrime — up to 198.2 per 100K. It still maintains strong laws and better performance than many states, but didn’t improve fast enough to hold its ground as others surged ahead.

10. Connecticut

2024 Rank: 19 → 2025 Rank: 10 (▲9)

Connecticut makes one of the most impressive climbs into the top 10. It lowered its breach rate significantly — from a sky-high 0.69 to 0.22 — and cybercrime stayed relatively contained at 155 per 100K. Add a full set of privacy protections, and this Northeast state has turned things around in just half a year.

This is the second year DesignRush has published this ranking. View the 2024 Data Security Index here to see how states have improved (or worsened) since last year.

10 Worst States for Data Privacy in 2025

The places where your personal information is most vulnerable — and why it matters

Rank (2025)	State	Score	Rank (2024)	Change
50	Alaska	63.08	49	▼ 1
49	Maine	69.47	43	▼ 6
48	Wyoming	79.41	35	▼ 13
47	Arizona	80.05	47	Same
46	Florida	80.46	46	Same
45	South Dakota	80.62	50	▲ 5
44	Wisconsin	80.99	41	▼ 3
43	Kansas	80.99	28	▼ 15
42	Michigan	81.49	14	▼ 28
41	Massachusetts	81.58	48	▲ 7

1. Alaska

2024 Rank: 49 → 2025 Rank: 50 (▼1)

Alaska now ranks dead last for data privacy in the U.S. — and it’s not even close. The state’s cybercrime rate skyrocketed to 914.7 per 100K residents, by far the worst in the nation. Even though its breach rate is moderate, Alaska continues to offer minimal legal protection (scoring just 1 out of 6). With no legislative progress and rising criminal activity, it’s the most dangerous state for your digital life.

2. Maine

2024 Rank: 43 → 2025 Rank: 49 (▼6)

Maine has the highest rate of data breaches in the country at 1.07 per 100K — a sharp increase from last year. While cybercrime levels are around average, the combination of widespread leaks and only basic legal safeguards (2 out of 6) leaves residents dangerously exposed. The state is in urgent need of modern privacy legislation.

3. Wyoming

2024 Rank: 35 → 2025 Rank: 48 (▼13)

Wyoming took one of the steepest dives this year, dropping 13 spots. Its cybercrime rate jumped to 234.3, and privacy laws remain stagnant at the lowest possible score. With no serious updates to its legal framework and growing threat levels, Wyoming is quickly becoming one of the riskiest states to live online.

4. Arizona

2024 Rank: 47 → 2025 Rank: 47 (Same)

Arizona remains stuck at the bottom. It still has one of the highest cybercrime rates in the nation (265.1 per 100K), and while its breach rate is relatively low (0.09), the state has made no progress on legislation — holding steady at 1 out of 6. Until that changes, Arizonans remain largely unprotected

5. Florida

2024 Rank: 46 → 2025 Rank: 46 (Same)

Despite its booming tech economy, Florida continues to underperform on data safety. Cybercrime remains high (223.3 per 100K), and the state has not strengthened its privacy protections at all. With only basic enforcement and a legal score of 1, Florida offers little peace of mind when it comes to personal information.

6. South Dakota

2024 Rank: 50 → 2025 Rank: 45 (▲5)

South Dakota made modest progress this year — its data breach rate dropped from 0.98 to 0.22. But that alone wasn’t enough to move it out of the bottom 10. It still lacks modern privacy legislation and remains vulnerable due to rising cybercrime (140.4 per 100K). Improvement is there, but the foundation is still weak.

7. Wisconsin

2024 Rank: 41 → 2025 Rank: 44 (▼3)

Wisconsin continues its slow slide down the rankings. Its data breach rate is now 0.17, and cybercrime is holding steady around 161. Still, with no meaningful privacy laws in place, the state has little to protect its residents from data misuse. It’s falling behind the national curve.

8. Kansas

2024 Rank: 28 → 2025 Rank: 43 (▼15)

Kansas suffered a sharp drop this year. Both cybercrime and breach rates ticked up (now at 161.5 and 0.17 respectively), and its privacy law score is still at rock bottom. With no legislative action and increasing digital threats, Kansas went from mid-tier to red-flag territory in just six months.

9. Michigan

2024 Rank: 14 → 2025 Rank: 42 (▼28)

Michigan had the biggest collapse in this year’s rankings. The state dropped a staggering 28 spots after its privacy law score was reduced from 5 to just 1 — a massive policy backslide. While its cybercrime and breach rates didn’t worsen dramatically, the lack of legal support erased earlier gains, leaving residents far more vulnerable than a year ago.

10. Massachusetts

2024 Rank: 48 → 2025 Rank: 41 (▲7)

Massachusetts managed to climb a few spots, thanks mostly to slightly improved enforcement. But its breach rate remains very high (0.45), and while it has better laws than most bottom-tier states (3 out of 6), they haven’t been enough to reverse course. The state is showing signs of momentum — but it's still far from secure.

Rank	State	Cybercrime Per Capita	Data Breaches Per Capita	Data Protection Laws Score	Final Data Safety Score
1	Kentucky	134.4	0.07	6	98.20
2	Montana	163.0	0.09	6	97.26
3	Tennessee	157.9	0.11	6	97.04
4	New Jersey	165.3	0.12	6	96.72
5	Utah	196.3	0.09	6	96.54
6	Iowa	221.9	0.06	6	96.48
7	Texas	199.3	0.09	6	96.47
8	Minnesota	159.9	0.16	6	96.18
9	Virginia	198.2	0.15	6	95.52
10	Connecticut	155.0	0.22	6	95.31
11	California	244.1	0.13	6	94.86
12	Oklahoma	182.6	0.07	5	94.16
13	Colorado	249.2	0.17	6	94.09
14	Nevada	328.0	0.09	6	93.69
15	Delaware	266.8	0.19	6	93.38
16	Indiana	341.7	0.10	6	93.24
17	Rhode Island	147.6	0.36	6	93.18
18	Vermont	144.5	0.00	4	93.13
19	New Hampshire	166.1	0.35	6	92.94
20	Maryland	239.4	0.26	6	92.83
21	Oregon	210.9	0.47	6	90.01
22	Mississippi	104.2	0.07	2	86.86
23	North Carolina	199.4	0.13	3	86.82
24	New York	183.6	0.16	3	86.67
25	Illinois	200.2	0.15	3	86.47
26	West Virginia	146.6	0.06	2	86.10
27	Arkansas	137.3	0.10	2	85.65
28	New Mexico	182.3	0.05	2	85.49
29	Alabama	152.0	0.10	2	85.33
30	South Carolina	176.3	0.07	2	85.30
31	Pennsylvania	212.8	0.21	3	85.22
32	Hawaii	180.0	0.07	2	85.22
33	Washington	226.3	0.08	2	84.06
34	Nebraska	129.8	0.05	1	83.63
35	Louisiana	140.4	0.04	1	83.57
36	Georgia	177.1	0.18	2	83.48
37	North Dakota	111.1	0.13	1	82.73
38	Idaho	153.9	0.10	1	82.29
39	Missouri	160.6	0.10	1	82.15
40	Ohio	209.7	0.04	1	82.07
41	Massachusetts	199.7	0.45	3	81.58
42	Michigan	160.8	0.14	1	81.49
43	Kansas	161.5	0.17	1	80.99
44	Wisconsin	161.4	0.17	1	80.99
45	South Dakota	140.4	0.22	1	80.62
46	Florida	223.3	0.12	1	80.46
47	Arizona	265.1	0.09	1	80.05
48	Wyoming	234.3	0.17	1	79.41
49	Maine	152.1	1.07	2	69.47
50	Alaska	914.7	0.27	1	63.08

Methodology: What We Measured (and Why)

To make this ranking meaningful and transparent, we weighted and normalized the data using trusted public sources:

Factor	Weight	Source
Cybercrime per capita	35%	FBI Internet Crime Report 2024
Data breaches per capita	35%	ITGovernanceUSA, Maine.gov
Privacy law score	30%	IAPP U.S. Privacy Tracker

For comparison, we also included last year’s 2024 scores, so you can see which states are improving, stagnating, or falling behind.

Read next: Which Jobs Face the Highest Risk of Automation, and Which Ones Are Likely Safe?

by Asim BN via Digital Information World

Which Jobs Face the Highest Risk of Automation, and Which Ones Are Likely Safe?

Automation is creeping into workplaces faster than ever, and not all jobs are built to survive the shift. A recent analysis by WillRobotTakeMyJob ranks 100 occupations that face the greatest risk of being replaced by machines, alongside 100 that appear safer, at least for now. The study uses machine learning models trained on U.S. Department of Labor data to estimate how likely a job is to be automated based on the skills, knowledge, and complexity it demands.

The results don't just show who might be vulnerable, but also who’s likely to keep a human edge in the age of artificial intelligence.

Where Automation Hits Hardest

Jobs that repeat the same steps each day, rely on limited decision-making, or involve manual labor in structured environments have the highest odds of being automated. Many of the top-ranked high-risk jobs involve physical tasks or simple data handling.

• Refuse and Recyclable Material Collectors top the list with a 100% risk score. They earn around $45,760 and face slow job growth.
• Packers and Packagers earn even less, roughly $34,800, and also hold a perfect risk rating. Like many warehouse roles, their work is predictable and easy to program.
• Machine Feeders, Offbearers, and Freight Laborers also fall into this category. They’re already being replaced by robotics in factories and fulfillment centers.

Other occupations flagged include dredge operators, billing clerks, shoe machine operators, and title examiners. These roles typically carry lower wages, ranging between $35,000 and $55,000, and have little demand for personal judgment or creative thinking.

Even jobs that once seemed secure, like credit analysts and customer service reps, now face high exposure. AI can quickly learn patterns in credit risk or handle scripted client queries, often more efficiently than a person can.

#	Occupation	Risk level	Job score	Risk level (voted)	Median wage (USD)	Projected growth (by 2031)
1	Refuse and Recyclable Material Collectors	100.00%	2.2/10	71.27%	45,760	2.30%
2	Packers and Packagers, Hand	100.00%	1.6/10	76.89%	34,830	-4.20%
3	Machine Feeders and Offbearers	100.00%	1.1/10	81.25%	39,250	-12.70%
4	Laborers and Freight, Stock, and Material Movers, Hand	100.00%	2.7/10	78.21%	37,660	4.20%
5	Fallers	100.00%	1.8/10	58.33%	53,170	-8.40%
6	Dredge Operators	100.00%	2.7/10	78.57%	50,440	2.10%
7	Shoe Machine Operators and Tenders	100.00%	0.4/10	91.16%	36,970	-13.60%
8	Credit Analysts	100.00%	3.0/10	68.90%	79,420	-3.90%
9	Title Examiners, Abstractors, and Searchers	100.00%	2.9/10	54.49%	53,550	1.00%
10	Billing and Posting Clerks	100.00%	2.2/10	81.08%	45,590	0.50%
11	Court Reporters and Simultaneous Captioners	100.00%	2.3/10	77.42%	63,940	1.80%
12	Postal Service Mail Sorters, Processors, and Processing Machine Operators	100.00%	2.2/10	72.37%	53,440	-7.90%
13	Cooks, Fast Food	100.00%	1.4/10	74.73%	29,260	-13.70%
14	Postal Service Mail Carriers	100.00%	3.1/10	53.84%	56,330	-3.00%
15	Bookkeeping, Accounting, and Auditing Clerks	100.00%	2.2/10	88.89%	47,440	-5.00%
16	Bill and Account Collectors	100.00%	1.8/10	68.18%	44,250	-9.50%
17	Telephone Operators	100.00%	0.7/10	85.88%	38,080	-26.40%
18	Motion Picture Projectionists	100.00%	0.9/10	72.66%	35,160	-5.00%
19	Correspondence Clerks	100.00%	1.6/10	83.33%	42,120	-6.70%
20	Receptionists and Information Clerks	100.00%	1.8/10	82.92%	35,840	-0.50%
21	Credit Authorizers, Checkers, and Clerks	100.00%	1.6/10	80.88%	48,000	-5.20%
22	Switchboard Operators, Including Answering Service	100.00%	0.9/10	83.70%	36,750	-25.20%
23	Brokerage Clerks	100.00%	2.4/10	58.55%	60,150	-2.80%
24	Production, Planning, and Expediting Clerks	100.00%	3.3/10	78.02%	53,900	4.90%
25	Insurance Claims and Policy Processing Clerks	100.00%	1.8/10	74.17%	46,900	-3.90%
26	Proofreaders and Copy Markers	100.00%	1.6/10	70.57%	48,790	-3.40%
27	Mail Clerks and Mail Machine Operators, Except Postal Service	100.00%	1.4/10	85.29%	36,880	-6.20%
28	Word Processors and Typists	100.00%	1.3/10	81.45%	46,450	-38.00%
29	Legal Secretaries and Administrative Assistants	100.00%	1.9/10	75.38%	50,680	-5.10%
30	Order Clerks	100.00%	1.2/10	78.91%	41,600	-17.90%
31	Office Machine Operators, Except Computer	100.00%	1.0/10	82.29%	37,450	-15.10%
32	Graders and Sorters, Agricultural Products	100.00%	1.0/10	78.70%	34,360	-4.70%
33	New Accounts Clerks	100.00%	1.3/10	80.85%	44,630	-14.60%
34	Data Entry Keyers	100.00%	1.1/10	90.60%	37,790	-25.00%
35	Food Batchmakers	100.00%	3.4/10	68.52%	38,460	9.10%
36	Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic	100.00%	3.0/10	70.00%	44,390	2.00%
37	Food Cooking Machine Operators and Tenders	100.00%	1.4/10	77.78%	38,550	1.00%
38	Slaughterers and Meat Packers	100.00%	1.9/10	69.32%	38,160	1.40%
39	Pressers, Textile, Garment, and Related Materials	100.00%	1.0/10	73.86%	32,240	-12.00%
40	Timing Device Assemblers and Adjusters	100.00%	2.0/10	87.50%	48,840	-16.30%
41	Shoe and Leather Workers and Repairers	100.00%	1.2/10	52.14%	36,020	-11.90%
42	Tool Grinders, Filers, and Sharpeners	100.00%	1.8/10	75.00%	46,410	-7.80%
43	Gem and Diamond Workers	100.00%	1.6/10	81.25%	47,450	-3.70%
44	Milling and Planning Machine Setters, Operators, and Tenders, Metal and Plastic	100.00%	1.0/10	80.95%	47,200	-12.90%
45	Helpers--Production Workers	100.00%	1.1/10	77.82%	36,700	-8.30%
46	Sewing Machine Operators	100.00%	1.3/10	70.24%	34,440	-13.20%
47	Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic	100.00%	1.8/10	70.00%	44,620	-19.20%
48	Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic	100.00%	2.1/10	67.31%	42,610	-10.70%
49	Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic	100.00%	1.6/10	64.06%	42,400	-11.20%
50	Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders	100.00%	1.6/10	67.86%	35,530	-8.80%
51	Textile Knitting and Weaving Machine Setters, Operators, and Tenders	100.00%	1.1/10	68.42%	37,130	-11.80%
52	Textile Bleaching and Dyeing Machine Operators and Tenders	100.00%	0.4/10	80.71%	35,340	-10.30%
53	Mixing and Blending Machine Setters, Operators, and Tenders	100.00%	3.5/10	86.54%	46,100	4.30%
54	Etchers and Engravers	100.00%	2.3/10	89.58%	40,040	2.30%
55	Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders	100.00%	2.0/10	80.65%	39,340	4.50%
56	Semiconductor Processing Technicians	100.00%	3.7/10	59.78%	45,850	13.00%
57	Ophthalmic Laboratory Technicians	100.00%	2.2/10	51.67%	37,720	1.60%
58	Sawing Machine Setters, Operators, and Tenders, Wood	100.00%	2.4/10	77.78%	38,000	-0.50%
59	Tire Builders	100.00%	2.2/10	75.00%	54,080	3.10%
60	Adhesive Bonding Machine Operators and Tenders	100.00%	2.3/10	56.25%	43,540	-0.50%
61	Cutters and Trimmers, Hand	100.00%	1.2/10	60.53%	37,040	-18.40%
62	Textile Cutting Machine Setters, Operators, and Tenders	100.00%	0.8/10	64.47%	36,620	-11.70%
63	Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic	100.00%	1.8/10	51.56%	47,110	-11.40%
64	Payroll and Timekeeping Clerks	100.00%	1.8/10	79.91%	52,240	-15.10%
65	Medical Transcriptionists	100.00%	1.3/10	77.31%	37,060	-4.70%
66	Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders	99.90%	2.7/10	68.75%	42,670	2.70%
67	Office Clerks, General	99.45%	1.8/10	77.10%	40,480	-5.60%
68	Judicial Law Clerks	99.32%	3.1/10	52.66%	57,490	3.40%
69	Cutting and Slicing Machine Setters, Operators, and Tenders	99.26%	1.5/10	79.41%	44,310	-2.70%
70	Tax Preparers	99.13%	2.8/10	73.44%	49,010	4.20%
71	Patternmakers, Metal and Plastic	98.97%	2.0/10	96.88%	49,670	-22.20%
72	Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic	98.36%	1.3/10	68.75%	44,240	-9.50%
73	Electromechanical Equipment Assemblers	98.24%	3.8/10	75.00%	40,490	7.20%
74	Bridge and Lock Tenders	98.20%	2.5/10	80.00%	49,120	0.50%
75	Gambling and Sports Book Writers and Runners	98.13%	1.2/10	57.43%	29,170	-2.40%
76	Court, Municipal, and License Clerks	97.59%	2.7/10	66.67%	46,110	3.80%
77	Woodworking Machine Setters, Operators, and Tenders, Except Sawing	97.54%	1.6/10	65.38%	38,260	-2.20%
78	Telemarketers	97.49%	0.9/10	90.40%	34,480	-21.50%
79	Glass Blowers, Molders, Benders, and Finishers	97.47%	3.6/10	51.92%	43,310	5.30%
80	Loading and Moving Machine Operators, Underground Mining	97.27%	2.5/10	60.00%	64,070	-22.90%
81	Parking Attendants	97.17%	2.4/10	81.63%	32,840	5.30%
82	Medical Records Specialists	97.09%	3.8/10	68.94%	48,780	8.70%
83	Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers	96.78%	2.2/10	75.00%	44,030	-3.10%
84	Farm Labor Contractors	96.63%	2.5/10	79.00%	45,730	6.60%
85	Gambling Cage Workers	96.46%	0.8/10	82.95%	36,110	-3.70%
86	Molders, Shapers, and Casters, Except Metal and Plastic	96.26%	3.6/10	77.50%	43,310	5.30%
87	Fast Food and Counter Workers	96.21%	2.7/10	87.56%	29,540	5.70%
88	Logging Equipment Operators	96.13%	2.1/10	61.25%	48,240	-3.80%
89	Couriers and Messengers	96.12%	3.0/10	68.75%	36,710	8.30%
90	Forging Machine Setters, Operators, and Tenders, Metal and Plastic	95.99%	1.0/10	77.50%	46,990	-15.70%
91	Financial Clerks	95.79%	2.0/10	86.64%	45,790	-6.10%
92	Ushers, Lobby Attendants, and Ticket Takers	95.58%	1.9/10	88.97%	29,780	2.60%
93	Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic	95.58%	1.8/10	76.47%	38,870	-2.50%
94	Secretaries and Administrative Assistants, Except Legal, Medical, and Executive	94.81%	2.7/10	71.64%	44,280	-0.30%
95	Sewers, Hand	94.46%	0.7/10	74.68%	32,240	-12.20%
96	Painting, Coating, and Decorating Workers	93.80%	2.1/10	52.99%	40,230	1.50%
97	Foundry Mold and Coremakers	93.73%	2.1/10	55.00%	44,300	-24.60%
98	Technical Writers	93.58%	4.0/10	55.64%	80,050	4.00%
99	Agricultural Equipment Operators	93.56%	3.9/10	79.17%	39,690	8.40%
100	Cytotechnologists	93.55%	4.2/10	70.00%	60,780	5.30%

It’s no coincidence that many of these jobs also show weak or negative growth projections through 2031. Technology isn't just changing the way these roles are done, it's starting to phase them out.

The Safer Side of the Job Market

On the flip side, some careers look far less vulnerable. Jobs that involve empathy, creative reasoning, or high-level strategy are proving harder for machines to replicate.

• Anthropologists and Archeologists are at the very bottom of the automation risk list, showing a 0% risk. Their work depends heavily on interpretation, deep context, and cultural insight.
• Emergency Management Directors also rank as safe. These professionals coordinate complex responses to disasters, which demand leadership, timing, and judgment.
• Security Managers, education administrators, and occupational therapists all show no risk of being automated, largely because their work hinges on decision-making and human interaction.

Medical professionals appear repeatedly throughout the low-risk list. Roles like internal medicine physicians, speech-language pathologists, and clinical psychologists not only involve personal care but require careful assessments that can’t be replicated with code. Median wages for these roles are significantly higher, often exceeding $90,000 or even $200,000 in physician roles.
.

#	Occupation	Risk level	Job score	Risk level (voted)	Median wage (USD)	Projected growth (by 2031)
1	Anthropologists and Archeologists	0.00%	7.5/10	19.18%	63,800	7.80%
2	Emergency Management Directors	0.00%	6.4/10	36.21%	83,960	4.00%
3	Security Managers	0.00%	8.0/10	25.53%	102,340	5.30%
4	Education Administrators, Kindergarten through Secondary	0.00%	7.3/10	26.12%	103,460	-0.50%
5	Fitness and Wellness Coordinators	0.00%	5.9/10	45.00%	57,570	6.90%
6	Civil Engineers	0.00%	8.5/10	28.04%	95,890	6.50%
7	General Internal Medicine Physicians	0.00%	7.5/10	33.05%	223,310	3.40%
8	Anthropology and Archeology Teachers, Postsecondary	0.00%	7.0/10	28.26%	93,650	3.80%
9	Social Work Teachers, Postsecondary	0.00%	6.6/10	25.00%	75,020	3.60%
10	Occupational Therapists	0.00%	8.9/10	19.39%	96,370	11.10%
11	Clinical Nurse Specialists	0.00%	8.5/10	23.28%	86,070	6.00%
12	First-Line Supervisors of Police and Detectives	0.00%	7.8/10	19.02%	101,750	3.80%
13	Hospitalists	0.00%	8.0/10	30.15%	236,000	3.90%
14	Neuropsychologists	0.00%	7.8/10	23.19%	117,750	5.00%
15	Neurologists	0.00%	8.2/10	21.89%	224,260	6.80%
16	Psychiatrists	0.00%	8.6/10	25.30%	226,880	7.60%
17	Coaches and Scouts	0.00%	7.5/10	22.33%	45,910	8.80%
18	Chief Executives	0.00%	8.3/10	24.14%	206,680	5.50%
19	Manufactured Building and Mobile Home Installers	0.00%	3.6/10	33.93%	38,980	-19.60%
20	Urologists	0.00%	8.5/10	21.74%	236,000	3.90%
21	Physical Therapists	0.00%	9.0/10	19.47%	99,710	14.20%
22	Choreographers	0.00%	6.5/10	22.81%	52,000	5.30%
23	Recreational Therapists	0.00%	6.5/10	24.14%	57,120	4.30%
24	Firefighters	0.00%	7.3/10	15.36%	57,120	4.20%
25	First-Line Supervisors of Firefighting and Prevention Workers	0.00%	7.5/10	26.32%	86,220	4.20%
26	Nurse Anesthetists	0.00%	8.0/10	36.07%	212,650	10.40%
27	Nurse Midwives	0.00%	8.1/10	23.31%	129,650	7.10%
28	Nurse Practitioners	0.00%	9.0/10	28.58%	126,260	46.30%
29	Dentists, General	0.00%	7.8/10	29.95%	166,300	4.80%
30	Physician Assistants	0.00%	8.7/10	30.79%	130,020	28.50%
31	Art Therapists	0.00%	7.8/10	22.46%	63,650	11.80%
32	Music Therapists	0.00%	7.0/10	37.79%	63,650	11.80%
33	Advanced Practice Psychiatric Nurses	0.00%	8.5/10	12.50%	86,070	6.00%
34	Physical Medicine and Rehabilitation Physicians	0.00%	8.2/10	25.74%	236,000	3.90%
35	Art, Drama, and Music Teachers, Postsecondary	0.00%	7.3/10	20.30%	80,360	2.70%
36	Sports Medicine Physicians	0.00%	8.5/10	15.79%	236,000	3.90%
37	Adapted Physical Education Specialists	0.00%	5.8/10	20.45%	67,190	2.10%
38	Preventive Medicine Physicians	0.00%	7.3/10	36.67%	236,000	3.90%
39	Emergency Medical Technicians	0.00%	7.0/10	14.09%	38,930	6.10%
40	Paramedics	0.00%	7.6/10	15.05%	53,180	5.90%
41	Psychology Teachers, Postsecondary	0.00%	6.9/10	35.17%	82,140	5.00%
42	Nursing Instructors and Teachers, Postsecondary	0.00%	7.5/10	42.65%	80,780	17.90%
43	Midwives	0.00%	7.4/10	16.28%	63,630	5.80%
44	Athletic Trainers	0.00%	7.5/10	27.22%	57,930	12.70%
45	Healthcare Social Workers	0.00%	8.1/10	23.05%	62,940	9.70%
46	Mental Health and Substance Abuse Social Workers	0.00%	8.0/10	11.22%	55,960	11.60%
47	Architecture Teachers, Postsecondary	0.00%	6.4/10	37.96%	105,770	3.20%
48	Architects, Except Landscape and Naval	0.00%	8.0/10	34.55%	93,310	7.80%
49	Landscape Architects	0.00%	6.7/10	36.82%	79,320	4.70%
50	Marriage and Family Therapists	0.00%	7.7/10	25.00%	58,510	16.20%
51	Mental Health Counselors	0.00%	8.0/10	27.51%	53,710	18.80%
52	Clinical Neuropsychologists	0.00%	7.6/10	28.47%	117,750	5.00%
53	Critical Care Nurses	0.00%	8.5/10	23.13%	86,070	6.00%
54	Physicists	0.58%	8.3/10	18.84%	155,680	7.20%
55	Urban and Regional Planners	0.64%	7.4/10	23.31%	81,800	4.30%
56	Chief Sustainability Officers	0.84%	8.1/10	33.33%	206,680	5.50%
57	Farm and Home Management Educators	0.92%	4.6/10	35.71%	59,770	-1.70%
58	Fish and Game Wardens	1.08%	5.6/10	18.53%	60,380	-5.00%
59	Bioengineers and Biomedical Engineers	1.45%	7.8/10	28.13%	100,730	7.40%
60	Biologists	1.48%	7.7/10	26.53%	91,100	5.60%
61	Orthotists and Prosthetists	1.78%	7.5/10	33.57%	78,100	15.10%
62	Park Naturalists	1.81%	7.4/10	17.71%	68,750	5.60%
63	Pediatricians, General	2.11%	7.5/10	22.67%	198,690	2.10%
64	Biochemists and Biophysicists	2.23%	8.0/10	30.37%	107,460	9.00%
65	Educational, Guidance, and Career Counselors and Advisors	2.41%	7.3/10	29.60%	61,710	4.50%
66	Environmental Restoration Planners	2.49%	7.0/10	25.00%	78,980	7.30%
67	Soil and Plant Scientists	2.78%	7.6/10	22.37%	68,240	7.20%
68	Exercise Trainers and Group Fitness Instructors	2.92%	7.0/10	35.98%	46,480	13.60%
69	Health Education Specialists	3.02%	6.9/10	34.00%	62,860	7.00%
70	Environmental Engineers	3.05%	8.0/10	29.65%	100,090	6.90%
71	Special Education Teachers, Secondary School	3.11%	6.8/10	25.00%	66,620	-0.60%
72	Construction Managers	3.15%	8.9/10	22.64%	104,900	9.10%
73	Naturopathic Physicians	3.16%	6.4/10	39.71%	107,990	2.60%
74	Agricultural Sciences Teachers, Postsecondary	3.54%	6.2/10	33.33%	85,260	4.80%
75	Clergy	3.79%	6.5/10	10.32%	58,920	2.50%
76	Substance Abuse and Behavioral Disorder Counselors	3.94%	8.2/10	21.57%	53,710	18.80%
77	Chiropractors	3.96%	8.0/10	20.15%	76,530	9.90%
78	Fire Inspectors and Investigators	4.15%	6.7/10	32.69%	74,160	4.50%
79	Exercise Physiologists	4.17%	6.4/10	40.63%	54,860	10.40%
80	Recreation and Fitness Studies Teachers, Postsecondary	4.65%	5.7/10	35.00%	75,770	3.40%
81	Biological Science Teachers, Postsecondary	5.15%	7.6/10	36.00%	83,920	8.40%
82	Directors, Religious Activities and Education	5.55%	5.7/10	30.30%	50,140	2.20%
83	Social and Community Service Managers	5.76%	8.1/10	26.06%	77,030	8.20%
84	Special Education Teachers, Elementary School	5.76%	6.5/10	16.41%	64,910	-0.70%
85	Special Education Teachers, Kindergarten	5.76%	6.5/10	19.05%	64,910	-0.70%
86	Acute Care Nurses	5.76%	7.4/10	15.63%	86,070	6.00%
87	Water/Wastewater Engineers	5.81%	8.5/10	16.25%	95,890	6.50%
88	Curators	6.11%	7.5/10	16.18%	61,750	12.20%
89	Industrial-Organizational Psychologists	6.28%	7.4/10	26.22%	147,420	5.80%
90	Police and Sheriff's Patrol Officers	6.40%	7.4/10	17.57%	72,280	3.90%
91	Range Managers	6.47%	6.2/10	44.44%	68,750	5.60%
92	Prosthodontists	6.49%	6.5/10	41.07%	234,000	3.50%
93	Education and Childcare Administrators, Preschool and Daycare	6.56%	5.7/10	23.53%	54,290	-2.10%
94	Water Resource Specialists	6.57%	7.6/10	47.92%	157,740	7.50%
95	Hydrologists	6.65%	6.3/10	25.00%	88,770	2.80%
96	Epidemiologists	6.71%	7.5/10	30.67%	81,390	18.80%
97	Veterinarians	6.83%	8.6/10	26.10%	119,100	19.10%
98	Electricians	6.84%	8.3/10	20.45%	61,590	10.80%
99	Fire-Prevention and Protection Engineers	7.08%	7.0/10	31.82%	103,690	5.10%
100	Health Specialties Teachers, Postsecondary	7.36%	7.7/10	38.46%	105,650	18.80%

The pattern is clear: the harder it is to standardize a job, the harder it is to automate.

What the Model Looks At

The risk scores came from a model trained using job data from O*NET, a database maintained by the U.S. Department of Labor. The model evaluated more than just job titles. It looked at dozens of traits per role, things like originality, manual precision, persuasion, scheduling, and social awareness. These attributes were measured both in terms of importance and level of difficulty.

Jobs that demand higher levels of abstract thinking, creative solutions, and interpersonal awareness were less likely to be marked as automatable. In contrast, tasks with fixed outcomes and clear inputs were labeled as easy targets.

The developers behind WillRobotTakeMyJob also factored in user feedback and manually labeled edge cases. The final scores came from a regression model, which had a high predictive accuracy of over 91%.

Lessons for the Working World

For workers, the list isn’t meant to cause panic. But it should raise a flag. If your role sits high on the risk chart, it might be time to rethink what you bring to the table. Learning new skills, cross-training, or moving into roles that require more thinking and less repetition could help with long-term career survival.

It’s also worth watching how companies use automation. Some may swap out workers for cost savings, while others might keep people in place but shift them into oversight, coordination, or technical roles. Jobs won’t vanish overnight, but the nature of how we work is already starting to tilt.

A Look Ahead

If there's one message from this data, it's that no job is guaranteed forever. But the ones that thrive will be those that keep people at the center, jobs that lean on our ability to think, connect, and adapt.

Whether you’re packing boxes or planning evacuations, the best way to stay ahead of the machines is to keep doing what they can’t.

Read next: Can AI Argue Better Than You? New Study Suggests It Might

by Irfan Ahmad via Digital Information World