iPhone Air Durability Tests Show Surprising Strength, but Trade-Offs and High Costs Remain

Apple’s thinnest smartphone to date, the iPhone Air, has already faced tough durability testing. Reviewers wanted to know if a device that measures only 5.6 millimeters thick could handle the stresses of everyday use.

The Air is part of the iPhone 17 lineup and arrives with big claims from Apple. Executives insisted it exceeds the company’s strength standards. They even challenged journalists to bend the phone in interviews. The bold statements raised eyebrows, especially since many still remember BendGate in 2014 when iPhone 6 models bent with relative ease.

Now, independent testing gives a clearer picture of how the Air performs. It also shows where compromises have been made.

Titanium Frame and Slim Build

The frame of the iPhone Air is made from Grade 5 titanium. The alloy is strong, light, and more elastic than aluminum. That elasticity lets it bend slightly under pressure and return to its original form instead of holding a permanent curve. Apple says most of the titanium is recycled, part of its sustainability push.

Measuring just 5.6 millimeters, the Air is thinner than three stacked quarters or half a Lego brick. This makes it the slimmest iPhone the company has ever released. Within the iPhone 17 series, only the Air carries titanium. The standard iPhone 17 and the 17 Pro use aluminum frames, a shift tied to weight and cost.

Display and Scratch Resistance

Apple fitted the phone with its second-generation Ceramic Shield, developed with Corning. The company says it is three times more resistant to scratches than earlier models.

Tests seem to back that up. Scratches that would normally appear at Mohs hardness level 6 were faint. Even at level 7, marks were minimal. For an iPhone screen, this is a marked improvement.

That said, glass remains glass. The Air may resist scratches better, but drops onto hard surfaces can still shatter the screen.

Bend Tests by Hand

The main question was whether such a thin device could survive bending. Reviewer Zack Nelson tried applying force with his hands. Pushing from the back produced no visible change. Flexing it from the front caused a brief curve, but the titanium frame straightened out again in minutes.

Image: JerryRigEverything/YouTube

The results contrast sharply with the iPhone 6 era. Back then, normal use could warp the frame permanently. With the Air, titanium seems to have solved that problem.

Breaking Point Under Measured Force

To find the exact pressure needed to snap the phone, Nelson set up a test using two metal bars and a crane scale. The phone was pressed in the center until the frame gave way.

The first crack was heard at 171 pounds of pressure. The device finally broke at 216 pounds. Even then, the back glass stayed intact, though the front glass fractured near the lower volume button.

That level of force is far greater than what most users could apply in normal life. An adult weighing 216 pounds would spread that weight across clothing and the whole phone surface when sitting down. In practice, pockets are far more likely to wear out before the iPhone Air bends.

Smaller Battery and Slower Charging

The thin profile does not come without cost. The iPhone Air carries a smaller battery than its Pro counterparts. It also charges more slowly. Apple says the Air reaches 50 percent in 30 minutes, while the 17 Pro manages the same in just 20 minutes.

The Air also lacks stereo speakers. It uses a single earpiece speaker, which limits audio depth. These are real trade-offs of the slim design.

Battery Life Across the 17 Series

In independent European testing, the iPhone 17 Pro Max lasted 53 hours on a single charge. That put it ahead of Samsung’s Galaxy S25 Ultra, which ran just under 45 hours, and Google’s Pixel 10 Pro XL at nearly 49 hours.

The iPhone Air managed about 40 hours. That result is close to Samsung’s S25 Edge, which also uses a smaller battery.

Apple rates its batteries for 1,000 charging cycles before they fall below 80 percent of their original capacity. Samsung doubles that figure with its Galaxy S25 range, promising 2,000 cycles. Google matches Apple at 1,000 cycles. So while the Air can last longer than some rivals on a single charge, its long-term endurance is not the strongest.

There are also regional differences. In the United States, the iPhone 17 Pro ships with only eSIM and a slightly larger battery. That version runs about two hours longer than the Indian model, which still uses a physical SIM slot.

Drop Tests and Repairability

Durability is not just about bending. In standardized European drop tests, the iPhone 17 Pro Max survived 180 falls before failure, earning a Class B grade. That is twice as strong as last year’s iPhone 16 Pro Max.

Competitors went further. Both Samsung’s Galaxy S25 Ultra and Google’s Pixel 10 Pro XL survived 270 drops. They earned Class A grades.

Repairability is another measure where Apple did not shine. The iPhone Air and the iPhone 17 Pro Max both received Class C ratings. Samsung scored the same, while Google’s Pixel achieved Class B.

Efficiency Gains

One area where Apple has taken the lead is efficiency. The iPhone 17 Pro Max received a Class A rating under the EU’s energy label system, an improvement from Class B the year before.

The gain came from the use of stacked battery cells and new vapor chamber cooling in the Pro and Pro Max. These changes help the phone stay cooler and hold charge during heavy workloads. The Air does not have all of those features, but the series as a whole benefits from the changes.

Price and Global Affordability

Performance aside, the cost remains high. The average selling price of a smartphone in 2025 is around 370 dollars. Apple’s iPhone 17 series starts near 799 dollars in the United States, with Pro models at 1,099 dollars or more.

That makes the iPhone far more expensive than the global average. For many consumers, it remains out of reach.

Measured in workdays, the gap is even clearer. In Luxembourg, buyers need about three days of wages for a Pro model. In the United States, it takes four days. In India, the number is closer to 160 days. Globally, the average is about 26 days, but the spread shows how uneven the affordability really is.

Apple has positioned the iPhone as a premium product. The iPhone Air fits that profile. It is slim, built with titanium, and priced well above the norm.

Lessons From BendGate to Today

Apple’s focus on the Air’s strength highlights how far the company has come since BendGate. In 2014, customers could bend the iPhone 6 with little effort. That episode left a mark on the brand.

The Air tells a different story. It can take more than 200 pounds of direct pressure before breaking. It shrugs off hand bending attempts. Its screen resists scratches better than earlier versions.

Still, not every measure favors Apple. Battery longevity, drop resilience, and repairability continue to trail competitors. And the price keeps the phone out of reach for many.

Outlook

The iPhone Air shows that a slim frame does not always mean weakness. Independent testing proves that titanium allows the phone to flex and recover without lasting damage. The device can survive far more pressure than anyone would apply in daily use.

Yet thinness has limits. Smaller batteries, slower charging, and weaker speakers are the cost of the design. Compared with rivals, Apple delivers efficiency and runtime, but not the strongest durability over years of use.

The high price makes the Air a premium choice rather than a mainstream one. For those who buy it, the device offers strength and refinement. For many others, it represents a product that remains desirable but unattainable.

Image: James A. Molnar / Unsplash

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

Read next: Staying Up Late Linked to Loneliness and Smartphone Problems Among University Students
by Irfan Ahmad via Digital Information World

Smartphone Prices to Climb Steadily Through 2029

Global smartphone prices are on a steady upward path. The average selling price is expected to move from 370 dollars in 2025 to 412 dollars by 2029. That growth rate works out to around three percent a year.

At the same time, revenue from smartphones is forecast to expand faster than prices. By 2029, worldwide sales could reach 564 billion dollars, supported by a five percent annual growth rate, as highlighted by CounterPointResearch in its Market Outlook Tracker.

Signs of Normalization

The smartphone market is showing more stable behavior after years of disruption. Shipments in 2025 are on track to rise about 2.5 percent compared with the previous year. That pace is slightly higher than earlier projections but slower than initial hopes. Higher prices, supply realignments, and wider economic pressure are the main reasons. With prices moving up more quickly than shipments, overall revenue is gaining strength.

Regional Shifts

In North America, the average price is expected to climb seven percent in 2025. The push comes from premium models, strong promotions, and growing interest in foldables. Prices in the region may reach close to 984 dollars in 2026.

China is on a slower path. Forecasts suggest a 3.6 percent increase in 2025, led by brands such as Huawei, OPPO, and vivo. Apple’s performance in China has also improved, helped by Pro model sales.

India remains a mid-range market. Average prices are still below 250 dollars this year but should rise gradually, reaching about 287 dollars in 2029. The shift from feature phones and stronger demand outside major cities are shaping this trend.

Company Profiles

Apple continues to lead the premium segment. Its prices are projected to rise from 919 dollars in 2025 to nearly 1,000 dollars in 2029. The company is widening its base with cheaper models for emerging markets while keeping its high-end focus with Pro devices. Analysts also expect an extra lift in 2026 with Apple’s first foldable release.

Samsung holds a more stable profile. Weak flagship sales in early 2025 lowered its average, though foldables and AI features are expected to provide support in the longer term. Huawei has been regaining ground in China. With fewer supply problems, its premium Mate and P series are driving prices higher, supported by strong foldable sales.

Product and Technology Factors

Generative AI smartphones added 40 to 60 dollars to production costs in 2024 and 2025. That raised prices at first. In the longer term, the perceived value of AI features is likely to keep average prices high even as costs stabilize. Foldables, though still a small fraction of global shipments, are also influencing price levels and setting new expectations for premium devices.

Outlook

The industry is heading for modest but steady growth. Tariff risks have eased, supply chains are more stable, and demand for advanced features is holding firm. Together, these factors suggest smartphone prices will continue to climb through 2029 at a controlled pace, keeping the market on a firmer footing than in recent years.

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

Read next: YouTube Leads Streaming as Prime Video Rises, but Category Suffers First Decline Since February

by Irfan Ahmad via Digital Information World

TikTok’s Shopping Test Raises Concern After Gaza Clips Flagged

TikTok is facing questions over a new test that uses image recognition to link videos with shopping items. The function, as spotted by TheVerge, appeared over the weekend in several regions and surprised viewers when it surfaced in footage from Gaza.

The system scans a paused frame, highlights clothing or accessories, and then suggests similar products from TikTok Shop. In one case, it identified a woman’s dress, scarf, and handbag as she searched through rubble and pulled up links to near-identical items. The same prompts appeared on humanitarian clips and children’s content.

According to TikTok, this was part of a limited trial that was not meant to apply in these contexts. The company said engineers are working to restrict where the tags appear. Access is still limited, and users can disable the option in their own settings.

The feature reflects a wider push by social media firms to blend shopping directly into feeds. Instagram and YouTube have adopted similar tools. For TikTok, visual search extends that model by letting any video act as a product trigger, not just those created for promotion.

The Gaza incident shows the risks of applying commerce engines without clear boundaries. Automated recognition treats every frame as material for sales, regardless of subject. That creates the chance that moments of personal tragedy or urgent appeals will be paired with ads for consumer goods.

Image: theverge

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

Read next: Nobel Laureates and Global Experts Push for Binding AI Safeguards
by Irfan Ahmad via Digital Information World

Nobel Laureates and Global Experts Push for Binding AI Safeguards

More than 200 leaders in science, politics, and technology have signed a declaration urging governments to set binding global limits on artificial intelligence. The Global Call for AI Red Lines was released at the United Nations General Assembly in New York at the start of its high-level week.

Who signed and who organized

The signatories include Nobel Prize winners in peace, chemistry, physics, and economics, alongside AI researchers such as Geoffrey Hinton, Yoshua Bengio, Ian Goodfellow, and OpenAI co-founder Wojciech Zaremba. Support also came from Anthropic’s security chief Jason Clinton and a range of civil society organizations. The initiative was coordinated by the French Center for AI Safety, the Future Society, and the Center for Human-Compatible Artificial Intelligence at UC Berkeley.

What the letter demands

The statement calls for governments to reach an international agreement by the end of 2026. It identifies specific areas that should be off-limits, including lethal autonomous weapons, self-replicating systems, and the use of AI in nuclear command. While the European Union’s AI Act and bilateral U.S.-China agreements cover some risks, there is no global framework that addresses them.

Why voluntary pledges fall short

Technology firms have already signed voluntary commitments with governments, including U.S. and U.K. safety pledges in recent years. Independent reviews suggest those companies meet only part of their promises. Critics argue that without binding rules, commercial pressure will outweigh public safety.

Concerns over AI risks

The appeal comes after several incidents have raised alarms about AI. Recent cases have highlighted its role in spreading misinformation, enabling surveillance, and causing social harm. Researchers also point to long-term threats such as mass unemployment, biological risks, and human rights abuses if the technology advances without limits.

Global context

Organizers compared the effort to past international agreements that banned biological weapons and harmful industrial chemicals. They argue that clear restrictions are needed before AI development accelerates further. More than 60 civil society groups have already joined the call, reflecting support from research institutes and advocacy groups around the world.

What comes next

The United Nations will launch its first diplomatic body on AI later this week. World leaders are expected to discuss how red lines could be defined, monitored, and enforced through international cooperation. The backers of the initiative stress that restrictions would not prevent economic growth, but instead provide guardrails for safe development.

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

Read next: 

• Digital Currencies Push Into Global Economic Rankings

• Malware Counts Climb Higher on Windows as macOS Sees Fewer Cases

by Irfan Ahmad via Digital Information World

Digital Currencies Push Into Global Economic Rankings

The cryptocurrency sector has crossed a point where its scale can be measured beside national economies. Current estimates place the total value of all coins and tokens at around 3.88 trillion dollars. That makes it larger than India’s economy and places it just behind Japan and Germany. The speed of this climb is striking. In the past year, the market more than doubled, and compared with 2023 the increase is close to threefold. Looking back five years, the value is nearly ten times higher.

Setting It Against Countries

Putting digital assets against the size of traditional economies highlights the change. At today’s level, the crypto market is roughly 80 percent above the output of Italy, Brazil, Canada, or Russia. It is twice the scale of South Korea, Spain, or Australia. Against Switzerland or Poland, it is several times greater. The comparison shows that what started as a niche technology has become large enough to sit in global economic tables.

Stock Market Benchmarks

When compared with stock exchanges, the picture is mixed. At 3.88 trillion dollars, crypto is ahead of the London Stock Exchange and the Toronto Stock Exchange. Yet it remains far smaller than the New York Stock Exchange, which is valued above 25 trillion dollars. This places crypto in the middle ground, larger than some national markets but still behind the biggest hubs of global finance.

An Uneven Landscape

The size of the sector does not tell the whole story. Out of more than nine thousand coins and tokens in circulation, the top ten account for more than ninety percent of total value. Most tokens trade below one dollar, and only a handful are worth hundreds or thousands. This leaves a picture of concentration, with a few dominant currencies shaping the market while thousands contribute very little.

What Lies Ahead

The first half of 2025 has shown both the promise and the fragility of this market. Regulation is developing, institutional investors are entering, and volatility continues to define trading patterns. The result is an industry that now stands at a global scale but still carries the risks of a sector in transition.

Country	GDP (nominal, 2023)	GDP (abbrev.)
United States	$27,720,700,000,000	27.721 trillion
China	$17,794,800,000,000	17.795 trillion
Germany	$4,525,700,000,000	4.526 trillion
Japan	$4,204,490,000,000	4.204 trillion
Crypto	$3,880,000,000,000	3.88 trillion
India	$3,567,550,000,000	3.568 trillion
United Kingdom	$3,380,850,000,000	3.381 trillion
France	$3,051,830,000,000	3.052 trillion
Italy	$2,300,940,000,000	2.301 trillion
Brazil	$2,173,670,000,000	2.174 trillion
Canada	$2,142,470,000,000	2.142 trillion
Russia	$2,021,420,000,000	2.021 trillion
Mexico	$1,789,110,000,000	1.789 trillion
Australia	$1,728,060,000,000	1.728 trillion
South Korea	$1,712,790,000,000	1.713 trillion
Spain	$1,620,090,000,000	1.62 trillion
Indonesia	$1,371,170,000,000	1.371 trillion
Netherlands	$1,154,360,000,000	1.154 trillion
Turkey	$1,118,250,000,000	1.118 trillion
Saudi Arabia	$1,067,580,000,000	1.068 trillion
Switzerland	$884,940,000,000	884.94 billion
Poland	$809,201,000,000	809.201 billion
Argentina	$646,075,000,000	646.075 billion
Belgium	$644,783,000,000	644.783 billion
Sweden	$584,960,000,000	584.96 billion
Ireland	$551,395,000,000	551.395 billion
Thailand	$514,969,000,000	514.969 billion
United Arab Emirates	$514,130,000,000	514.13 billion
Israel	$513,611,000,000	513.611 billion
Austria	$511,685,000,000	511.685 billion
Singapore	$501,428,000,000	501.428 billion
Norway	$485,311,000,000	485.311 billion
Bangladesh	$437,415,000,000	437.415 billion
Philippines	$437,146,000,000	437.146 billion
Vietnam	$429,717,000,000	429.717 billion
Denmark	$407,092,000,000	407.092 billion
Iran	$404,626,000,000	404.626 billion
Malaysia	$399,705,000,000	399.705 billion
Egypt	$396,002,000,000	396.002 billion
Hong Kong	$380,812,000,000	380.812 billion
South Africa	$380,699,000,000	380.699 billion
Nigeria	$363,846,000,000	363.846 billion
Colombia	$363,494,000,000	363.494 billion
Romania	$350,776,000,000	350.776 billion
Czech Republic (Czechia)	$343,208,000,000	343.208 billion
Pakistan	$337,912,000,000	337.912 billion
Chile	$335,533,000,000	335.533 billion
Finland	$295,532,000,000	295.532 billion
Portugal	$289,114,000,000	289.114 billion
Peru	$267,603,000,000	267.603 billion
Kazakhstan	$262,642,000,000	262.642 billion
New Zealand	$252,176,000,000	252.176 billion
Iraq	$250,843,000,000	250.843 billion
Algeria	$247,626,000,000	247.626 billion
Greece	$243,498,000,000	243.498 billion
Qatar	$213,003,000,000	213.003 billion
Hungary	$212,389,000,000	212.389 billion
Ukraine	$178,757,000,000	178.757 billion
Kuwait	$163,705,000,000	163.705 billion
Ethiopia	$163,698,000,000	163.698 billion
Morocco	$144,417,000,000	144.417 billion
Slovakia	$132,908,000,000	132.908 billion
Dominican Republic	$121,444,000,000	121.444 billion
Ecuador	$118,845,000,000	118.845 billion
Sudan	$109,266,000,000	109.266 billion
Oman	$108,811,000,000	108.811 billion
Kenya	$108,039,000,000	108.039 billion
Guatemala	$104,450,000,000	104.45 billion
Bulgaria	$102,408,000,000	102.408 billion
Uzbekistan	$101,592,000,000	101.592 billion
Costa Rica	$86,497,941,439	86.498 billion
Luxembourg	$85,755,006,124	85.755 billion
Angola	$84,824,654,482	84.825 billion
Croatia	$84,393,795,502	84.394 billion
Sri Lanka	$84,356,863,744	84.357 billion
Panama	$83,318,176,900	83.318 billion
Serbia	$81,342,660,752	81.343 billion
Lithuania	$79,789,877,416	79.79 billion
Tanzania	$79,062,403,821	79.062 billion
Côte d'Ivoire	$78,875,489,245	78.875 billion
Uruguay	$77,240,830,877	77.241 billion
Ghana	$76,370,396,722	76.37 billion
Azerbaijan	$72,356,176,471	72.356 billion
Belarus	$71,857,382,746	71.857 billion
Slovenia	$69,148,468,417	69.148 billion
Myanmar	$66,757,619,000	66.758 billion
DR Congo	$66,383,287,003	66.383 billion
Turkmenistan	$60,628,857,143	60.629 billion
Jordan	$50,967,475,352	50.967 billion
Cameroon	$49,279,410,983	49.279 billion
Uganda	$48,768,955,863	48.769 billion
Tunisia	$48,529,595,417	48.53 billion
Bahrain	$46,079,867,021	46.08 billion
Macao	$45,803,067,940	45.803 billion
Bolivia	$45,135,398,009	45.135 billion
Libya	$45,096,462,972	45.096 billion
Paraguay	$42,956,263,544	42.956 billion
Cambodia	$42,335,646,896	42.336 billion
Latvia	$42,247,850,065	42.248 billion
Estonia	$41,291,245,222	41.291 billion
Nepal	$40,908,073,367	40.908 billion
Zimbabwe	$35,231,367,886	35.231 billion
Honduras	$34,400,509,852	34.401 billion
El Salvador	$34,015,620,000	34.016 billion
Cyprus	$33,886,930,712	33.887 billion
Iceland	$31,325,116,556	31.325 billion
Senegal	$30,848,333,084	30.848 billion
Georgia	$30,777,833,585	30.778 billion
Papua New Guinea	$30,729,242,919	30.729 billion
Zambia	$27,577,956,471	27.578 billion
Bosnia and Herzegovina	$27,514,782,476	27.515 billion
Trinidad and Tobago	$27,372,285,698	27.372 billion
Armenia	$24,085,749,592	24.086 billion
Albania	$23,547,179,830	23.547 billion
Malta	$22,328,640,242	22.329 billion
Guinea	$22,199,409,741	22.199 billion
Mozambique	$20,954,220,984	20.954 billion
Mali	$20,661,794,596	20.662 billion
Mongolia	$20,325,121,394	20.325 billion
Burkina Faso	$20,324,617,845	20.325 billion
Haiti	$19,850,829,758	19.851 billion
Benin	$19,676,049,076	19.676 billion
Jamaica	$19,423,355,409	19.423 billion
Botswana	$19,396,084,498	19.396 billion
Gabon	$19,388,402,542	19.388 billion
Nicaragua	$17,829,218,219	17.829 billion
State of Palestine	$17,420,800,000	17.421 billion
Afghanistan	$17,233,051,620	17.233 billion
Guyana	$17,159,509,565	17.16 billion
Niger	$16,819,170,421	16.819 billion
Moldova	$16,539,436,547	16.539 billion
Laos	$15,843,155,731	15.843 billion
Madagascar	$15,790,113,247	15.79 billion
North Macedonia	$15,763,621,848	15.764 billion
Congo	$15,321,055,823	15.321 billion
Brunei	$15,128,292,981	15.128 billion
Mauritius	$14,644,524,819	14.645 billion
Bahamas	$14,338,500,000	14.338 billion
Rwanda	$14,097,768,472	14.098 billion
Kyrgyzstan	$13,987,627,909	13.988 billion
Chad	$13,149,325,362	13.149 billion
Malawi	$12,712,150,082	12.712 billion
Namibia	$12,351,025,067	12.351 billion
Equatorial Guinea	$12,337,550,584	12.338 billion
Tajikistan	$12,060,602,009	12.061 billion
Mauritania	$10,651,709,411	10.652 billion
Togo	$9,171,261,838	9.171 billion
Montenegro	$7,530,593,375	7.531 billion
Barbados	$6,720,733,200	6.721 billion
Maldives	$6,590,894,302	6.591 billion
Sierra Leone	$6,411,869,546	6.412 billion
Fiji	$5,442,046,565	5.442 billion
Eswatini	$4,442,875,788	4.443 billion
Liberia	$4,240,000,000	4.24 billion
Andorra	$3,785,067,332	3.785 billion
Aruba	$3,648,573,136	3.649 billion
Suriname	$3,455,146,281	3.455 billion
Belize	$3,066,850,000	3.067 billion
Burundi	$2,642,161,669	2.642 billion
Central African Republic	$2,555,492,085	2.555 billion
Cabo Verde	$2,533,819,406	2.534 billion
Saint Lucia	$2,430,148,148	2.43 billion
Gambia	$2,396,111,022	2.396 billion
Seychelles	$2,141,450,171	2.141 billion
Lesotho	$2,117,962,451	2.118 billion
Timor-Leste	$2,079,916,900	2.08 billion
Guinea-Bissau	$2,048,348,108	2.048 billion
Antigua and Barbuda	$2,033,085,185	2.033 billion
Solomon Islands	$1,633,319,401	1.633 billion
Comoros	$1,352,380,971	1.352 billion
Grenada	$1,316,733,333	1.317 billion
Vanuatu	$1,126,313,359	1.126 billion
St. Vincent & Grenadines	$1,065,962,963	1.066 billion
Saint Kitts & Nevis	$1,055,499,778	1.055 billion
Samoa	$938,189,444	938.189 million
Sao Tome & Principe	$678,976,265	678.976 million
Dominica	$653,992,593	653.993 million
Micronesia	$460,000,000	460 million
Palau	$281,849,063	281.849 million
Kiribati	$279,208,903	279.209 million
Marshall Islands	$259,300,000	259.3 million
Tuvalu	$62,280,312	62.28 million

Read next: Malware Counts Climb Higher on Windows as macOS Sees Fewer Cases
by Asim BN via Digital Information World

Malware Counts Climb Higher on Windows as macOS Sees Fewer Cases

Fresh data from 2025 shows that Windows computers continue to attract the bulk of malware activity. Surfshark Antivirus recorded close to 479,000 detections from January through late August. Out of that total, about 419,000 were on Windows devices and just over 60,000 were on macOS. The difference puts Windows at nearly seven times the number of infections seen on Apple systems.

Market Share Shapes Attacks

One reason behind the imbalance is the larger share of Windows in the desktop market. Globally, Windows accounts for around 71 percent of users, while macOS holds about 15 percent. The picture is similar across individual regions. In the United States and the United Kingdom, Windows has about two thirds of the share. In Germany, France, and Spain it ranges from 70 to 72 percent, while in South Korea it climbs as high as 85 percent. Attackers lean toward platforms that promise the widest reach, and the scale of Windows keeps it at the top of their list.

Malware Types on macOS

Although the raw numbers on Apple machines remain smaller, the data makes clear that macOS faces its own risks. Viruses accounted for the largest portion at 28 percent. Trojans followed at 26 percent. Riskware came in at 15 percent, adware at 8 percent, and exploits at 7 percent, while the rest fell into less common categories. Each carries a different method of operation, from malicious code that attaches to programs to software that appears legitimate but opens a pathway for further attacks.

Windows Categories and July Surge

On Windows, the most common detections involved malicious PowerShell scripts, which made up 22 percent of the total. Trojans represented 21 percent, viruses 17 percent, heuristic detections 14 percent, and potentially unwanted applications 11 percent. The reliance on PowerShell was most visible in July, when detections rose to 100,000. That figure was more than double the monthly average of 47,000. More than half of those infections were linked to PowerShell-based attacks that coincided with known flaws in Microsoft’s SharePoint software. April and May also showed smaller peaks with 13,000 and 23,000 detections tied to the same method.

Importance of Timely Updates

MacOS did not show spikes of that scale, although some variation appeared, such as a rise in trojans during May. Even with fewer cases overall, the platform still recorded a share of threats designed to exploit unpatched systems. About 7 percent of detections on macOS fell into this category. This pattern underscores the need for users to keep their systems updated. Both Microsoft and Apple issue regular patches to close security gaps, and the data shows how quickly attackers try to take advantage of those who delay applying them.

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

Read next: AI Bias in Healthcare: How Small Language Shifts Affect Women and Minority Patients
by Irfan Ahmad via Digital Information World

AI Bias in Healthcare: How Small Language Shifts Affect Women and Minority Patients

Medical research has often leaned on data from white men. Women and minority patients were left out of many past trials. That gap now shows up in artificial intelligence. Models trained on these records are being used in hospitals and clinics, and the shortcomings are visible in their recommendations.

Findings from MIT’s study

A team at the Massachusetts Institute of Technology tested four large language models, including GPT-4, Llama 3 (two different variants), and Palmyra-Med. They wanted to see how models respond when patient questions are slightly altered in ways that don’t change the medical facts. The changes included shifting gender markers, removing gender entirely, adding typos or extra spaces, and rewriting in anxious or dramatic tones.

Even with the same clinical information, treatment recommendations changed by about seven to nine percent on average. The direction of change often meant less medical care. For example, some patients who should have been advised to seek professional help were told instead to manage their symptoms at home.

Groups most affected

The errors hit some groups harder. Female patients faced more recommendations for reduced care than men, even when the cases were identical. In one test, whitespace errors led to seven percent more mistakes for women compared with men. The problem extended to other groups as well. Non-binary patients, people writing in anxious or emotional tones, those with limited English, and those with low digital literacy also saw weaker results.

Removing gender markers did not solve the issue. The models inferred gender and other traits from writing style and context, which meant disparities continued.

Drop in conversation accuracy

The researchers also tested models in conversational exchanges that mirrored chat-based patient tools. Accuracy dropped by around seven percent across all models once these small changes were introduced. These settings are closer to real-world use, where people type informally, include errors, or express emotion in their writing. In those cases, female patients again saw more frequent advice to avoid care that would have been necessary.

Evidence from other studies

The MIT work is not the only warning sign. A study from the London School of Economics reported that Google’s Gemma model consistently downplayed women’s health needs. A Lancet paper from last year found GPT-4 produced treatment plans linked to race, gender, and ethnicity rather than sticking to clinical information. Other researchers found that people of color seeking mental health support were met with less compassionate responses from AI tools compared with white patients.

Even models built for medicine are vulnerable. Palmyra-Med, designed to focus on clinical reasoning, showed the same pattern of inconsistency. And Google’s Med-Gemini model recently drew criticism when it produced a fake anatomical part, showing that errors can range from obvious to subtle. The obvious ones are easier to catch, but biases are less visible and may pass through unchecked.

Risks for deployment in healthcare

These findings come as technology firms move quickly to market their systems to hospitals. Google, Meta, and OpenAI see healthcare as a major growth area. Yet the evidence shows language models are sensitive to non-clinical details in ways that affect patient care. Small variations in writing can shift recommendations, and the impact often falls on groups already disadvantaged in medicine.

The results point to the need for stronger checks before rolling out AI systems in patient care. Testing must go beyond demographics to include writing style, tone, and errors that are common in real-world communication. Without this, hospitals may end up deploying tools that quietly reproduce medical inequality.

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

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by Irfan Ahmad via Digital Information World