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

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

A recent study with 900 people found that an AI tool can sometimes do a better job than humans when it comes to changing someone’s opinion during a conversation. The researchers set up a special debate platform online, where participants discussed different topics in a back-and-forth format. They were randomly assigned to argue either for or against a topic, even if it wasn’t their real opinion.

Each person was placed in one of twelve groups based on three things: whether they were debating a human or the AI, whether their opponent had access to personal information like age or politics, and how strongly they felt about the topic before the debate began.

When the AI had no personal details, it was about as persuasive as a person. But when it knew even small facts about someone, like how old they were or what political group they identified with, it became much more convincing. In debates where the AI and the human didn’t do equally well, the AI came out ahead about 64% of the time. The researchers said this meant a “more than 80 percent” jump in the chance that the AI could get someone to change their mind.

The AI only used six basic details about each person. These were age, gender, race, education level, job status, and political leanings. Even with just this limited data and a very short instruction, it still managed to tailor its arguments in ways that worked. The authors said the AI was told to “astutely use this information to craft arguments that are more likely to persuade and convince.” On the other hand, people who had the same information about their opponent didn’t do any better. The AI used what it knew more strategically.

What’s surprising is that the AI didn’t change how it spoke when it used that personal data. It didn’t become more emotional or more casual. It used the same clear and logical tone every time. The researchers explained that the AI’s success didn’t come from how it made its points, but from what it chose to say. One example was a debate about basic income: the AI explained it as an innovation tool to right-leaning people and as a way to reduce inequality to left-leaning ones.

Another interesting result had to do with how people felt about who they were talking to. Most could tell when they were arguing with the AI. But those who thought they were debating a machine were actually more likely to shift their views. The researchers don’t know if this was because the AI seemed less threatening or if people guessed it was AI because it was more persuasive. They said people “could have been more lenient” when they believed a machine was on the other side.

• Also read: Study Uncovers Gender-Based Disparities in Career Advice from Popular AI Models

The topic itself also mattered. The AI was much better at changing minds on issues where people had weaker opinions. But when the topic was highly personal or political, the AI’s advantage mostly disappeared. This backs up older research showing that strong opinions are hard to change, no matter how the message is delivered.

The debates didn’t take place in everyday conversation settings. People followed a fixed structure, had limited time, and had to argue a side even if they disagreed with it. Everyone was anonymous and paid to participate. Because of these limits, the results might not apply directly to the way people talk and argue online in real life.

Still, the results were clear. Even with short instructions and only basic information, the AI managed to pick arguments that worked. The study said stronger effects might be possible if the AI had more details about a person or better custom-made prompts. Even with simple input, it adapted with “unusual precision.”

The authors said this raises real concerns. AI that can tailor arguments to individuals could be used in quiet, hard-to-trace ways online. There’s no proof yet that this changed recent elections, but the researchers warned that “any large-scale deployment of bots” could influence public opinion in ways we don’t see.

At the same time, the study said this power could be used to help people too. If used carefully, persuasive AI might be good at reducing belief in conspiracy theories or helping people form better habits. The authors said, “There’s a real opportunity to turn what could be a threat into something deeply empowering.”

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

Read next: Analysis Reveals Generative AI May Save 12% of Economy’s Labor Time Through Task Acceleration
by Web Desk via Digital Information World

WhatsApp Tests Smarter Support, Brings Ads to Status, and Prepares Private AI Recaps

WhatsApp, as per WBI, is testing several new features that could soon reshape how people get help, view sponsored content, and catch up on conversations. These tools, currently available in various Android beta versions, reflect the app’s broader shift toward automation, visibility for creators, and private AI-powered convenience.

AI-Based Support Replaces Old Contact Forms

Until recently, asking WhatsApp for help meant filling out a form, adding a few screenshots, and hoping someone eventually replied. That system is now being replaced by something a bit more direct. Users opening the Help Center are being redirected to a chat where a support bot takes over. Instead of guessing which article fits their problem, users describe their issue in plain language and the system tries to match it with relevant answers. If the bot can’t solve it, the conversation can be passed along to a human agent.

This new support flow skips the form entirely. The AI asks follow-up questions, pulls up suggestions from WhatsApp’s help library, and offers step-by-step guidance. It’s already live for some users in the standard app, even though it’s still tagged as a beta feature. The aim here is to reduce waiting time and cut down on vague interactions that often lead nowhere.

Ads Quietly Appear in Status and Channels

WhatsApp is also beginning to show ads in parts of the app that never had them before. Some users in the beta program have started to see Status Ads and Promoted Channels inside the Updates tab. These changes mark the start of a more visible advertising strategy that stays clear of private chats and group threads.

Status Ads work a bit like Instagram stories from brands. They show up between regular status updates and can be skipped with a swipe. While they don’t interrupt conversations, they do blend into the same space where friends and contacts post updates. Each one is labeled clearly so people can spot a sponsored post at a glance. If a certain advertiser gets too pushy, there’s a quick option to block them entirely.

Promoted Channels follow a similar pattern. These are public channels that pay for extra visibility, making them more likely to show up when users browse or search. These placements are flagged as sponsored and appear alongside organic channels in the directory. It’s a new way for creators and organizations to grow an audience without relying entirely on word of mouth.

• Also read: Beyond Safety: Location Sharing Becomes Emotional Anchor in Gen Z’s Daily Lives

To help users track what they’ve seen, WhatsApp is rolling out a feature that creates an ad activity report. This log lists which ads were shown, when they appeared, and which advertisers paid for them. The report can be downloaded as a ZIP file, so users can archive or review it whenever they like. There’s also an option to have the report generated automatically every month.

While advertising may feel like a big shift for a messaging app, WhatsApp says it’s keeping things tight on privacy. Ads won’t appear inside chats, and the app still doesn’t read private messages or listen to calls. The ad system pulls from public activity, language settings, rough location, and followed channels, with users free to opt in or out of data sharing across Meta platforms. Importantly, phone numbers and private content remain off-limits to advertisers.

AI Chat Recaps Coming Soon

The third feature, still in development, is designed for people who don’t always have time to scroll through long chats. WhatsApp is working on a tool called Quick Recap, which gives users a short summary of unread messages from selected conversations. It’s built on Meta’s Private Processing system, which ensures that summaries stay secure and unreadable by WhatsApp or Meta itself.

Here’s how it works. You choose up to five chats, press the Quick Recap button, and within moments, the app presents a digest of what you missed. The summaries are stored locally and generated using encrypted data. This keeps private chats protected while still offering a bit of AI-powered convenience.

Not all chats are eligible. Conversations marked with Advanced Chat Privacy won’t be included in recaps. And the feature isn’t turned on by default. If you want to use it, you’ll need to switch it on in your settings.

Gradual Rollout, Big Shift

All three features are being tested in stages and aren’t available to everyone just yet. But taken together, they show how WhatsApp is evolving. From replacing old support forms with live AI bots, to building tools that make ads more transparent, and adding optional AI recaps for busy users, the app is clearly adapting to changing habits. Whether or not these changes catch on, the direction is clear — faster help, smarter tools, and more control over what users see and share.

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

Read next: LinkedIn Plans to Remove Hashtag Feed as Platforms Shift Discovery Methods
by Asim BN via Digital Information World