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AI & the Jobs Market: Which Professions Will Vanish by 2030 ...
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AI & the Jobs Market: Which Professions Will Vanish by 2030 and How to Thrive in the New Reality?
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https://codegym.cc
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[] |
AI might eliminate 85 million jobs in just a year but create 97 million new ones. By 2030, 375 million people will be forced to change careers due to the ...
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The summary:
The Current State of AI Technologies Development
AI Evolution Timeline
2020 , COVID-19, the University of Oxford develops Curial — a rapid AI test for emergency rooms. The AI proves its efficiency in handling extreme situations. Meanwhile, OpenAI releases GPT-3 with 175 billion parameters for humanlike text generation, making a breakthrough in NLP.
, COVID-19, the University of Oxford develops Curial — a rapid AI test for emergency rooms. The AI proves its efficiency in handling extreme situations. Meanwhile, OpenAI releases GPT-3 with 175 billion parameters for humanlike text generation, making a breakthrough in NLP. 2022 — OpenAI launches ChatGPT, and five days after the launch, the app acquired over 1 million users. Thus, the greatest exposure to using AI on a daily basis begins.
The Numbers Behind the Top AI Tools
24 Billion: the number of online visits generated by the top 50 AI tools in 1 year
the number of online visits generated by the top 50 AI tools in 1 year 14 Billion: the number of visits generated by ChatGPT alone during that period
the number of visits generated by ChatGPT alone during that period 5.5 Billion: the number of visits generated by the US, followed by India (2.1 billion) and Indonesia (1.4 billion)
The Increasing Number of Open Source AI
AI Adoption Across Industries: Which Ones Are Ahead
Making The Headlines
Airbnb acquires an AI startup for close to $200 million to build the ‘ultimate travel agent”,
Google’s AI weather forecaster beats a global standard and gives more accurate forecasts than Europe’s leading weather center,
Industries That Prioritize The Implementation of AI in Their Operations
The retail sector leads in AI implementation, with 72% of retailers using AI. 80% of retail executives expect to adopt AI automation by 2025,
68% of healthcare organizations use AI technologies,
63% of IT and telecom companies utilize AI,
44% of automotive organizations implement AI. By 2035, 75% of vehicles will be equipped with AI technology,
25% of travel and hospitality companies already use chatbots and other AI technologies.
Impact Of AI On Jobs And Employment: Who’s at Risk
Predictions about the impact of AI on the global job market in 2024-2025
By 2025, AI will eliminate 85 million jobs. Instead, it’ll create 97 million new ones,
AI and ML might replace 16% of US jobs by 2025,
Content creators and entry-level professionals across different industries believe their jobs are at risk because of AI.
What's next? Key AI Predictions Up to 2030
Intelligent robots might take the place of 30% of the global workforce.
375 million professionals may change careers by 2030.
Nearly a third of UK jobs could be replaced by AI in the 2030s.
Professions That Are Already at Risk.
Entry-level data analysts and researchers. AI can overtake manual and repetitive data entry tasks, minimizing human errors and allowing specialists to focus on strategic tasks.
AI can overtake manual and repetitive data entry tasks, minimizing human errors and allowing specialists to focus on strategic tasks. Customer service specialists. AI-driven tools, such as chatbots, automated phone systems, and knowledge-based systems (F.A.Qs, interactive troubleshooting guides), have successfully replaced the L1 support in service companies.
AI-driven tools, such as chatbots, automated phone systems, and knowledge-based systems (F.A.Qs, interactive troubleshooting guides), have successfully replaced the L1 support in service companies. Entry-level finance and accounting specialists. Potentially automated tasks include data collection, data entry, categorization, reconciliation, and invoicing.
Potentially automated tasks include data collection, data entry, categorization, reconciliation, and invoicing. Entry-level legal workers. This scope of tasks includes document automation and contract review.
This scope of tasks includes document automation and contract review. Travel agents. As automation tools become more advanced, many booking services are removed from the agents’ hands.
The Future of AI-Influenced Job Market: Which Professions Will Be Beneficial
Enhanced productivity in daily tasks: forget about manual tasks and focus on strategic and complex tasks.
forget about manual tasks and focus on strategic and complex tasks. More means of expression for creation: use AI for drafting and brainstorming.
use AI for drafting and brainstorming. New job sectors and career perspectives: AI-based digital assistants, smart devices, and robotic systems require specialists in development and support.
AI-based digital assistants, smart devices, and robotic systems require specialists in development and support. Easier upskilling: Implementing AI in businesses requires lifelong learning. At the same time, utilizing AI to gain new skills makes the education process far more efficient.
Implementing AI in businesses requires lifelong learning. At the same time, utilizing AI to gain new skills makes the education process far more efficient. Elevation of human expertise: there are plenty of professions that require creativity, empathy, strategic thinking, and human judgment that are less susceptible to being replaced by AI.
New professions that will emerge thanks to AI
Prompt engineers, who are skilled at the development and refinement of prompts for apps like ChatGPT to achieve the desired output,
who are skilled at the development and refinement of prompts for apps like ChatGPT to achieve the desired output, AI sales and marketing specialists who know the AI capabilities, can explain the benefits and “market” the AI solutions to businesses and consumers,
can explain the benefits and “market” the AI solutions to businesses and consumers, AI content editors and fact-checkers will be responsible for reviewing AI-generated content to ensure it is accurate, aligns with the company’s tone of voice, and free from biases.
will be responsible for reviewing AI-generated content to ensure it is accurate, aligns with the company’s tone of voice, and free from biases. Etc.
According to data from the World Economic Forum report, by 2030, 6-9% of people will be employed in jobs that do not exist today because of the impact of AI and automation. Now is the best time to embrace those changes and make the decision for your future career.
Industries in which automation will create the most job openings
Wrap-up
Shortly, developers will be in the highest demand.
How long does it take to become proficient in software development? You can make it by 2025
What are the best programming languages for software and AI development?
AI might eliminate 85 million jobs in just a year but create 97 million new ones. By 2030, 375 million people will be forced to change careers due to the implementation of AI in business processes across all industries. If you’re unsure how to feel about these facts — panic or rejoice because of the new opportunities — let’s examine today the transformation of the jobs market due to AI development. We’ll review the current state of AI & business synergy and get to the point where we decide on the most and the least promising careers.Aside from tech enthusiasts who’d taken an interest in AI a long time ago, most people barely paid attention to this field until the introduction of ChatGPT and the increasing information bubble about the threats of AI taking our jobs. However, AI has been around for quite some time and has been widely used in research, education, and business processes for many years already:So, what has changed recently? Let’s pinpoint two significant milestones:Companies that develop AI products attract massive investments, while tech giants reallocate their budgets to in-house AI development, starting the “arms race” in the age of AI.Here are just a few numbers for you to understand how huge the AI trend is today:From multitool like ChatGPT to highly specialized products like Grammarly for improving your writing and Respeecher for speech processing, AI companies are emerging all over the globe:What’s more important is that since 2020, there’s been a spike in AI development that is beneficial for business processes and encourages the easy integration of AI into any kind of enterprise.According to GitHub, the number of AI-related GitHub projects has significantly increased, growing from 1,536 in 2011 to 347,934 in 2022. See that spike between 2019 and 2020? Yeah, that’s when the accelerated changes in the perception of AI's influence on the business and the jobs market have begun:Based on the recent news, it may seem that AI is indeed everywhere and inevitably merging into business and governmental action plans:The UK’s Department for Transport wants flying taxis to take off inside the country as soon as 2026, with driverless versions coming several years later.So, are the forecasters, travel agents, and taxi drivers the only ones “threatened” by AI in the near future? Do they need to feel pressured at all? To predict these kinds of changes, it’s wise to consider industry trends and the level of economic development in various countries.As for now, the leading industries in AI adoption are retail, IT&Telecom, healthcare, automotive industry, and travel & hospitality:However, cross-industry data proves that the increasing adoption of AI is just a matter of time for almost any field. Executives see the potential of utilizing these technologies to transform their business processes. A third of businesses already use AI, and 9 of 10 companies believe that AI can gain them an edge over competitors. Nearly 4 out of 5 companies prioritized AI in business strategy.All in all, AI influence is inevitable in any business field. Which brings us to the main question: How will it affect human professionals? Will AI replace jobs?First and most importantly, advanced economies are prone to transform businesses with the help of AI faster than emerging and low-income countries:This means the automation trend may affect 38% of US jobs, 35% in Germany, 30% in the UK, and 21% in Japan.AI has a reputation as a productivity booster. However, some roles may be at risk of total automation.As you can see, AI may be a threat only for mundane and manual tasks. And, of course, its development is far from the human level of critical thinking and empathy. If you’re feeling anxious, don’t. Here’s a bonus: the list of 119 Jobs That AI Won't Replace Let’s reiterate the critical thought: AI is not a threat. It’s a resource that gives us access to unlimited opportunities, such as:According to global research from the World Economic Forum , half of organizations believe that AI will create job growth in the next five years. While many jobs are tech-related, non-techies can benefit from AI implementation. A few examples of non-tech emerging roles include:What is the safest option in a rapidly changing, tech-oriented world heavily relying on AI technologies? You know the answer. Become one of those who create new solutions, automate processes, and implement and support new technologies. The number of jobs in Artificial Intelligence and Information Technology (IT) will definitely increase. Data engineers, data scientists, computer vision engineers, and IT professionals specializing in technology development and automation will stay in hot demand by 2030.While AI creates new jobs for non-techies, the greatest share of irreplaceable future careers lies in the tech industry.With AI tools, a developer can create a product that automates the work of dozens, even hundreds, of people. Of course, those who create AI solutions will be the most desired specialists among the top companies.Java, Python, and C++. Since you’re conveniently reading this on a Java learning platform, let’s give Java a shot!
| 2030-07-14T00:00:00 |
2030/07/14
|
https://codegym.cc/groups/posts/25745-ai--the-jobs-market-which-professions-will-vanish-by-2030-and-how-to-thrive-in-the-new-reality
|
[
{
"date": "2024/04/09",
"position": 71,
"query": "AI employment"
},
{
"date": "2024/04/09",
"position": 14,
"query": "AI job creation vs elimination"
},
{
"date": "2024/04/09",
"position": 9,
"query": "AI labor market trends"
}
] |
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] |
AI Will Wipe Out White-Collar Jobs by 2027
|
The End of White Collar Work
|
https://www.wbn.digital
|
[] |
AI experts at Anthropic warn that nearly all white collar jobs could be automated by 2027. With little time left, companies and individuals must urgently ...
|
By Elke Porter | WBN Ai | June 9, 2025
Subscription to WBN and being a Writer is FREE!
In a striking new video from AI Copium, researcher Sholto Douglas of Anthropic predicts that by 2027–2028, AI systems will be capable of automating nearly every white-collar job. And it’s not just a prediction—it’s a warning echoed by other leading voices in the AI space, including Trenton Bricken (Anthropic), David Blondon (Data Stage), and futurist Peter Diamandis.
🔍 Key Takeaways:
White-collar automation is inevitable and imminent. Sholto Douglas claims that with existing models and enough data, we can already automate the majority of white-collar tasks—even if AI development stopped progressing.
Sholto Douglas claims that with existing models and enough data, we can already automate the majority of white-collar tasks—even if AI development stopped progressing. We don’t even need new AI models. According to Douglas and Bricken, current systems, with the right infrastructure and datasets, can handle most tasks done by analysts, consultants, marketers, HR, and even software engineers.
According to Douglas and Bricken, current systems, with the right infrastructure and datasets, can handle most tasks done by analysts, consultants, marketers, HR, and even software engineers. It’s not just technically possible—it’s economically inevitable. Companies will be financially incentivized to adopt AI to stay competitive. Those that don’t will risk being left behind.
Companies will be to adopt AI to stay competitive. Those that don’t will risk being left behind. Job displacement will begin fast and soon. Expect major disruption between 2026 and 2028 . Many workers, including those in Silicon Valley, are already feeling the effects, with layoffs accelerating.
Expect major disruption between . Many workers, including those in Silicon Valley, are already feeling the effects, with layoffs accelerating. Corporations are focused on profit, not people. Engineers who helped build these AI systems are being replaced by them. This cycle is expected to spread across industries.
Engineers who helped build these AI systems are being replaced by them. This cycle is expected to spread across industries. Most people, governments, and companies are unprepared. Experts urge immediate action: employers must train their workers to become AI users now—or risk making them obsolete.
Experts urge immediate action: employers must train their workers to become AI users now—or risk making them obsolete. Unanswered questions remain. What happens when consumers no longer have jobs or income to support the economy? The video notes that even if the economics don't add up in the long term, short-term profit motives will still drive adoption.
⚠️ Final Message:
The video concludes with a sense of urgency: this future is not decades away—it’s a few years out. While AI can improve lives and unlock abundance in medicine and robotics, without preparation, it will first cause mass disruption.
🎙️ Credit:
This summary is based on “AI Copium – Intro”, a video commentary on the future of artificial intelligence and work, featuring Sholto Douglas and Trenton Bricken of Anthropic, with insights from Peter Diamandis and David Blondon.
Why Does It Matter?
The prediction that AI could automate nearly all white-collar jobs by 2027–2030 matters because it signals a rapid and massive shift in the global workforce that few are prepared for. This could lead to widespread job displacement, economic disruption, rising inequality, and social unrest if proactive steps aren't taken. It’s a critical moment to rethink education, upskilling, and public policy to ensure AI enhances human potential rather than replaces it entirely.
🎙️ Bottom Line:
This isn’t just a temporary downturn — it’s a fundamental reset of the workforce. The future belongs to those who adapt.
Connect with Elke at Westcoast German Media or on LinkedIn: Elke Porter or contact her on WhatsApp: +1 604 828 8788
TAGS: #AI Job Disruption #Future Of Work #White Collar AI #AI Revolution #Anthropic Insights #Automation 2027 #WBN News Vancouver #Elke Porter
| 2027-08-07T00:00:00 |
2027/08/07
|
https://www.wbn.digital/ai-will-wipe-out-white-collar-jobs-by-2027-and-no-ones-ready/
|
[
{
"date": "2025/06/09",
"position": 61,
"query": "artificial intelligence blue collar workers"
},
{
"date": "2025/06/09",
"position": 38,
"query": "artificial intelligence white collar workers"
}
] |
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] |
Enhancing AI literacy in undergraduate pre-medical education ...
|
Enhancing AI literacy in undergraduate pre-medical education through student associations: an educational intervention - BMC Medical Education
|
https://bmcmededuc.biomedcentral.com
|
[
"Hopson",
"Department Of Physics",
"Astronomy",
"Brigham Young University",
"Provo",
"Mildon",
"Hassard",
"Kubalek",
"Laverty",
"Urie"
] |
However, a gap exists in formal AI education for pre-medical students. This study evaluates the effectiveness of the AI in Medicine Association ...
|
Study design
This study employed a quasi-experimental, pretest-posttest control group design to evaluate the educational impact of a student-led AI curriculum. Participants were assigned to either an intervention group, which completed the curriculum through the AI in Medicine Association (AIM), or a control group, which did not receive the intervention. Outcomes were assessed through knowledge gains in AI and pathology-related content.
Participants and recruitment
Participants were undergraduate students at BYU pursuing pre-medical or other pre-health career paths. Cohort participants were recruited via flyers, campus bulletins, and an in-person booth at BYU’s student center. Control group participants were recruited through in-person outreach in large, pre-med-focused courses. Inclusion criteria required current enrollment in pre-medical coursework and interest in healthcare careers. Students with prior formal AI training beyond the scope of the AIM curriculum were excluded.
Intervention
The AIM curriculum consisted of four weekly educational sessions incorporating principles of active learning and multimodal instruction, as recommended in the literature [10,11,12,13]. The curriculum integrated foundational AI concepts, ethical frameworks, hands-on engagement with histological image analysis, and exposure to current AI research. Specific topics included:
1. Introduction to AI in healthcare. 2. Ethical implications and responsible use of AI. 3. Data preprocessing techniques. 4. Model development, training, and evaluation.
Instructional materials were designed by AIM student officers and reviewed by a senior faculty member to ensure academic rigor and pedagogical clarity. A key project involved identifying cancerous tissue and histological features in whole-slide prostate images, fostering practical engagement with AI in pathology [20].
Assessment design
The primary assessment tool consisted of a structured survey administered both pre- and post-intervention. It began with six demographic/background questions (e.g., prior AI exposure, graduation year, attitudes toward AI) followed by ten knowledge items divided into two domains:
AI and Data Science (5 questions).
Pathology and AIM Projects (5 questions).
Item formats included multiple-choice and short-answer questions. A complete version of the assessment is available in Supplementary Materials.
Data collection
Both the intervention and control groups completed the same assessment before and after a four-week period. Assessments were conducted in supervised or distraction-free environments. Only cohort participants who completed all four AIM sessions were eligible for the posttest. Control participants received their posttest four weeks after the pretest, with no exposure to the intervention.
To reduce response bias, participants were assured that their responses would remain anonymous, were not graded for performance, and could omit questions if desired. Identifying information was removed from scores once collected, and only used to contact students if needed, to link pre- and post-tests to the same student, and to collect demographic information that was not collected in the survey such as the sex of the participant. Participation was voluntary, and all students were informed they could withdraw at any time. Those who opted out of the study were still allowed to engage fully in AIM activities. Data were collected over two academic semesters and included 15 intervention participants and 16 controls.
Grading and scoring
Responses were graded by a faculty member using a structured rubric to ensure consistency and minimize bias. Partial credit was awarded for partially correct answers, with specific criteria delineated in the rubric (see Supplementary Materials).
Statistical analysis
Descriptive statistics (means, standard deviations, medians, frequencies, and percentages) were used to summarize demographic variables and baseline characteristics. Between-group comparisons at baseline were assessed using chi-square tests (categorical variables) and independent t-tests or Mann-Whitney U tests (continuous variables).
To assess knowledge gains, within-group changes in pretest and posttest scores were analyzed using paired t-tests (or Wilcoxon signed-rank tests if data were non-normally distributed). Between-group comparisons of posttest scores were analyzed using independent t-tests or Mann-Whitney U tests.
Effect sizes were calculated using Cohen’s d. Additionally, an analysis of covariance was conducted to compare posttest scores between groups while controlling for pretest scores and potential confounders (e.g., prior AI experience, pre-med status).
Exploratory analyses included Pearson or Spearman correlations between prior AI experience and knowledge gains. A multiple regression model was used to identify predictors of improvement, with group assignment, prior AI experience, and baseline attitudes toward AI entered as independent variables.
Data visualization
To visualize score distributions and changes, violin plots were generated for pre- and posttest scores by group. Bar plots with error bars depicted mean score changes and standard deviations across AI, pathology, and combined domains. Scatter plots explored associations between prior experience or attitudes and test performance. All figures were generated using Python packages seaborn and matplotlib.
Ethical considerations
The study received approval from the Brigham Young University Institutional Review Board. All participants provided informed consent, and data confidentiality was maintained via secure storage and anonymized analysis (see Supplementary Material).
| 2025-12-14T00:00:00 |
2025/12/14
|
https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-025-07556-2
|
[
{
"date": "2022/12/01",
"position": 86,
"query": "AI education"
},
{
"date": "2023/03/01",
"position": 83,
"query": "AI education"
},
{
"date": "2023/06/01",
"position": 84,
"query": "AI education"
},
{
"date": "2023/09/01",
"position": 85,
"query": "AI education"
},
{
"date": "2023/11/01",
"position": 86,
"query": "AI education"
},
{
"date": "2024/01/01",
"position": 89,
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},
{
"date": "2024/03/01",
"position": 87,
"query": "AI education"
},
{
"date": "2024/05/01",
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},
{
"date": "2024/07/01",
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},
{
"date": "2024/10/01",
"position": 88,
"query": "AI education"
},
{
"date": "2024/11/01",
"position": 87,
"query": "AI education"
}
] |
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Implementing Artificial Intelligence in Critical Care Medicine
|
Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22 - Critical Care
|
https://ccforum.biomedcentral.com
| ["Cecconi","Humanitas University","Milan","Irccs Humanitas Research Hospital","Greco","Shickel","Int(...TRUNCATED) | "A social contract for AI in healthcare should define clear roles and responsibilities for all stake(...TRUNCATED) | "Artificial intelligence (AI) is rapidly entering critical care, where it holds the potential to imp(...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://ccforum.biomedcentral.com/articles/10.1186/s13054-025-05532-2
| [{"date":"2022/12/01","position":90,"query":"artificial intelligence healthcare"},{"date":"2023/01/0(...TRUNCATED) | [-0.0003744942951016128,0.03039797581732273,-0.01964176818728447,-0.0002922882267739624,-0.001191074(...TRUNCATED) |
Evaluating accountability, transparency, and bias in AI-assisted ...
| "Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qua(...TRUNCATED) |
https://bmcmedethics.biomedcentral.com
| ["Nouis","Saoudi Ce","Biochemistry Department","Worcester Royal Hospital","Worcester","Master Of Bus(...TRUNCATED) | "Forty participants—including clinicians, healthcare administrators, and AI developers—took part(...TRUNCATED) | "Aim, design, and setting\n\nThe main aim of this study was to explore how healthcare professionals (...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-025-01243-z
| [{"date":"2023/01/01","position":94,"query":"AI healthcare"},{"date":"2023/02/01","position":95,"que(...TRUNCATED) | [-0.0003380719281267375,0.029232431203126907,-0.02382328175008297,-0.0034382634330540895,-0.00123000(...TRUNCATED) |
Global Trends in Education: Artificial Intelligence ...
| "Global Trends in Education: Artificial Intelligence, Postplagiarism, and Future-focused Learning fo(...TRUNCATED) |
https://edintegrity.biomedcentral.com
| ["Eaton","Sarah Elaine","Werklund School Of Education","University Of Calgary","Calgary","Sarah Elai(...TRUNCATED) | "by SE Eaton · 2025 · Cited by 4 — In this distinguished research lecture, Dr. Sarah Elaine Eato(...TRUNCATED) | "Good guys versus bad guys\n\nStudents have been cheating for as long as there have been examination(...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://edintegrity.biomedcentral.com/articles/10.1007/s40979-025-00187-6
|
[
{
"date": "2025/03/01",
"position": 6,
"query": "artificial intelligence education"
}
] | [-0.0004054378077853471,0.014428495429456234,-0.02746068499982357,0.0017671998357400298,-0.001338126(...TRUNCATED) |
AI and the economic divide: How Artificial Intelligence could widen ...
| "AI and the economic divide: How Artificial Intelligence could widen the divide in the U.S. - EPJ Da(...TRUNCATED) |
https://epjdatascience.springeropen.com
| ["Septiandri","Nokia Bell Labs","Cambridge","Constantinides","Cyens Centre Of Excellence","Nicosia",(...TRUNCATED) | "These dynamics suggest that AI could amplify existing divides, hitting hardest in areas where econo(...TRUNCATED) | "4.1 Most- and least-impacted geographical areas\n\nJust as with the occupation analysis, the AII me(...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-025-00547-9
| [{"date":"2025/04/17","position":45,"query":"AI economic disruption"},{"date":"2025/04/17","position(...TRUNCATED) | [-0.0003783794236369431,0.03516018018126488,0.020490702241659164,-0.018162213265895844,-0.0013243280(...TRUNCATED) |
Radiology AI and sustainability paradox: environmental, economic ...
| "Radiology AI and sustainability paradox: environmental, economic, and social dimensions - Insights (...TRUNCATED) |
https://insightsimaging.springeropen.com
| ["Kocak","Department Of Radiology","University Of Health Sciences","Basaksehir Cam","Sakura City Hos(...TRUNCATED) | "AI systems, particularly deep learning models, require substantial computational resources, leading(...TRUNCATED) | "Environmental impact and challenges\n\nThe process of training an AI model, particularly those base(...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-01962-2
|
[
{
"date": "2025/04/17",
"position": 91,
"query": "AI economic disruption"
}
] | [-0.0002545317984186113,0.04428136348724365,-0.04129868000745773,0.02179652638733387,-0.000899823673(...TRUNCATED) |
Generative AI and its disruptive challenge to journalism
|
Generative AI and its disruptive challenge to journalism: an institutional analysis
|
https://link.springer.com
| ["Lewis","Seth C.","Sclewis Uoregon.Edu","University Of Oregon","Eugene","United States","Guzman","A(...TRUNCATED) | "by SC Lewis · 2025 · Cited by 3 — This conceptual article examines the transformative impact of(...TRUNCATED) | "It has long been anticipated, with various degrees of hope, hype, and hysteria, that artificial int(...TRUNCATED) | 2025-12-14T00:00:00 |
2025/12/14
|
https://link.springer.com/article/10.1007/s44382-025-00008-x
| [{"date":"2025/06/01","position":23,"query":"AI journalism"},{"date":"2025/06/01","position":17,"que(...TRUNCATED) | [-0.00043141364585608244,0.04712822288274765,-0.04736624285578728,0.012496119365096092,-0.0019636759(...TRUNCATED) |
Healthcare workers' readiness for artificial intelligence and ...
| "Healthcare workers' readiness for artificial intelligence and organizational change: a quantitative(...TRUNCATED) |
https://bmchealthservres.biomedcentral.com
| ["Boyacı","Fikret Biyal Central Research Laboratory","Cerrahpasa Medical Faculty","Istanbul Univers(...TRUNCATED) | "The aim of the study is to measure the readiness levels of medical artificial intelligence and the (...TRUNCATED) | "Technology offers new solutions to improve the quality of healthcare and facilitate access [1]. The(...TRUNCATED) | 2025-12-07T00:00:00 |
2025/12/07
|
https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-025-12846-y
| [{"date":"2025/06/08","position":21,"query":"artificial intelligence healthcare workers"},{"date":"2(...TRUNCATED) | [-0.000480843911645934,0.015739379450678825,-0.03711674362421036,-0.013918778859078884,-0.0015563191(...TRUNCATED) |
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