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1000 results for “enhance_dev”
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Just like numerous development teams globally, our QA team is also delving into ChatGPT to enhance their work efficiency. Here's a brief insight from our QA team on their initial experience of utilizing ChatGPT for crafting test cases. https://blog.oursky.com/2023/04/14/ai-vs-human-test-case-generation/ 🚀🌐 #QA #ChatGPT #efficiency #testcases
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Bitfrost and Stacks Foundation Team up to Enhance Bitcoin Utility - In a recent development, the Bitfrost Foundation has allied with the Stacks Founda... - https://news.bitcoin.com/bitfrost-and-stacks-foundation-team-up-to-enhance-bitcoin-utility/ #mitchellcuevas #stackslayer #blockchain #stablecoin #dohyunpak #bitfrost #layertwo #btc/usd #stacks #btcfi #l2
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https://buff.ly/3IX8XGB #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3oLHYqI #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://buff.ly/3NNp62K #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance
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https://t.co/7wK5BP2IM8 #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance https://t.co/PK77Vr3nWi
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https://t.co/7wK5BP3gBG #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance https://t.co/nmD6Che2F6
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https://t.co/7wK5BP2IM8 #Developers face various challenges when developing #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance https://t.co/LNWwQSfNAi
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https://t.co/7wK5BP2IM8 #Developers face an array of challenges when trying to develop #performant applications for Microsoft SQL Server. This course includes concepts and strategies that can help you enhance your app's performance on #SQL Server. #sqlserver #performance https://t.co/qv9WIANiM3
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Boost Your Ryzen Gaming Performance with a New Windows 11 Update
Microsoft has rolled out a new update for Windows 11 that brings significant performance improvements for Ryzen CPU users. If you have a Ryzen CPU, here’s how you can take advantage of these updates to enhance your gaming experience.
Why This Update Matters for Ryzen Users
Are you looking for better gaming performance on your Ryzen-powered PC? The new Windows 11 update, KB5041587, could be your answer. This update focuses on optimizing the way Windows 11 works with AMD Ryzen CPUs, including popular models like the Ryzen 7800X3D and 9700X.
Previously, these improvements were planned for the Windows 11 24H2 update. However, Microsoft has now included them in the existing 23H2 version. This means you don’t have to wait for the 24H2 release to enjoy better performance in your games.
How to Install the Update for Better Performance
To get the performance boost, you need to download the KB5041587 update manually. Follow these steps to install it:
- Go to Settings on your Windows 11 PC.
- Click on Windows Update.
- Select Advanced Options.
- Go to Optional Updates and find KB5041587.
- Download and install the update.
Once installed, you can expect up to a 10-11% performance boost in several games when playing at 1080p, depending on your Ryzen CPU model.
What Users and Experts Are Saying
Reviews are already pouring in, and the results are promising. Tests on the older Ryzen 7700X have shown a 10% improvement in gaming performance. Meanwhile, the newer Ryzen 9700X sees an 11% increase on average across various games. This means smoother gameplay and higher frame rates, making the update a must-have for gamers.
Hardware Unboxed and other tech reviewers have confirmed these findings, noting that the optimizations in AMD-specific branch prediction code make a noticeable difference in gaming performance.
Final Thoughts
If you own a Ryzen desktop CPU and are running Windows 11, don’t miss out on this easy way to improve your gaming experience. Just a simple update can lead to smoother gameplay and better performance across your favorite titles.
So, head over to Windows Update now and make sure you’re getting the best out of your Ryzen processor!
https://pixelbyte.dev/2024/08/29/boost-your-ryzen-cpu-with-windows-11-update-for-better-gaming/
#AMDRyzen #computerHardware #CPUOptimization #gamingBoost #gamingPerformance #microsoft #MicrosoftUpdates #news #PCGaming #RyzenUpdate #tech #TechNews #Windows11
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Bitfrost and Stacks Foundation Team up to Enhance Bitcoin Utility - In a recent development, the Bitfrost Foundation has allied with the Stacks Founda... - https://news.bitcoin.com/bitfrost-and-stacks-foundation-team-up-to-enhance-bitcoin-utility/ #mitchellcuevas #stackslayer #blockchain #stablecoin #dohyunpak #bitfrost #layertwo #btc/usd #stacks #btcfi #l2
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Bitfrost and Stacks Foundation Team up to Enhance Bitcoin Utility - In a recent development, the Bitfrost Foundation has allied with the Stacks Founda... - https://news.bitcoin.com/bitfrost-and-stacks-foundation-team-up-to-enhance-bitcoin-utility/ #mitchellcuevas #stackslayer #blockchain #stablecoin #dohyunpak #bitfrost #layertwo #btc/usd #stacks #btcfi #l2
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Bitfrost and Stacks Foundation Team up to Enhance Bitcoin Utility - In a recent development, the Bitfrost Foundation has allied with the Stacks Founda... - https://news.bitcoin.com/bitfrost-and-stacks-foundation-team-up-to-enhance-bitcoin-utility/ #mitchellcuevas #stackslayer #blockchain #stablecoin #dohyunpak #bitfrost #layertwo #btc/usd #stacks #btcfi #l2
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Sources: DOGE is rapidly developing GSAi, a custom generative AI chatbot for the US GSA to enhance productivity, analyze procurement data, and more! 💼🤖 #AI #GenerativeAI #DOGE #TechNews #GovernmentTech #Productivity #GSA #AIChatbot #Innovation
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You've developed your application using Google Kubernetes Engine and set up StatefulSets. Now, you're looking to enhance their reliability and especially their failover capabilities. That's where the Google Stateful HA Operator comes in. If you're interested in learning how to set it up and understanding its advantages and disadvantages from a customer perspective, read on.
https://blog.touret.info/2025/03/24/gcp-stateful-ha-operator/
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#Russia's Ministry of Digital Development plans to spend nearly 60 billion roubles ($660 million) over the next five years to enhance its #Internet #censorship system known as Technical Measures to Combat Threats (#TSPU), reports Reuters citing Forbes Russia. The goal is seemingly to strengthen tools that block virtual private networks (#VPN) and restrict access to content deemed illegal or restricted by the Russian government.
https://www.tomshardware.com/tech-industry/russia-to-spend-dollar660-million-to-strengthen-its-internet-censorship-infrastructure-report -
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DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
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-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
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Mindful Practices for Chronic Pain Relief and Emotional Wellness
Photo by Keenan Constance on Pexels.comChronic pain manifests in various forms, complicating life and diminishing joy. Whether stemming from autoimmune diseases, arthritis, fibromyalgia, or other chronic conditions, it not only impacts physical health but also has profound emotional and psychological effects that can lead to feelings of isolation and hopelessness. This multifaceted experience often challenges our daily routines, leading individuals to navigate a world that frequently seems unforgiving. To counteract these struggles, embark on a gentle meditative journey that encourages us to fully experience the body as it is, without judgment, and to cultivate awareness of our inner sensations and emotional states. By incorporating techniques such as mindfulness and visualization, we can ease our pain through the transformative power of gratitude, fostering a deeper connection with ourselves and nurturing resilience amidst adversity.
Body Scan
A body scan incorporated into meditation can be a gentle way to ease chronic pain, offering a pathway to greater mindfulness and enhanced body awareness. As we embark on a body scan, we lovingly direct our attention to various parts of our body, acknowledging sensations or tension without judgment. This compassionate practice allows us to recognize and alleviate the anxiety and stress that often accompany chronic pain, paving the way for a more peaceful experience. By embracing relaxation, we help to release muscle tension and foster a deeper connection with ourselves, empowering us to manage our pain responses more effectively. As we cultivate acceptance and compassion towards our pain, we may discover a reduction in discomfort and an uplift in our overall well-being.
Photo by Elina Fairytale on Pexels.comVisualization
Visualization in meditation can be a powerful ally in easing chronic pain, as it fosters a gentle mental picture of relaxation and healing, potentially transforming the way we experience pain. By engaging in focused imagery, we can nurture our minds, leading to a reduction in stress and an increase in the release of endorphins, the body’s natural pain relievers. This calming approach allows patients to create a distance from their discomfort, offering a renewed sense of control over their pain management journey. Moreover, visualization techniques can deepen mindfulness, empowering individuals to navigate their pain more effectively by reshaping emotional responses and alleviating anxiety tied to chronic conditions.
Affirmation
Affirmations like: I am in control of my body; Each breath brings me healing and relaxation; Pain is a temporary experience; I am strong and resilient; I embrace comfort and release tension, can genuinely transform how we perceive chronic pain by nurturing a sense of empowerment and mindfulness. By regularly uttering these gentle affirmations, we can forge a deeper bond with our physical sensations and emotional states. This nurturing practice invites a shift from seeing pain merely as an enemy to acknowledging it as a part of their unique journey, fostering personal growth and resilience. Furthermore, embracing the transient nature of pain can cultivate a profound appreciation for moments of relief, ultimately enhancing one’s overall well-being. In the end, such affirmations help to create a compassionate mental space where hope and positivity can blossom, leading to improved coping strategies and a more fulfilling life, even amid the challenges of chronic pain.
Gratitude
Photo by Summer Stock on Pexels.comThese tools offer unique ways to navigate the challenges of chronic pain, allowing glimmers of hope to shine through the clouds of distress we may face each day. I can personally empathize with how challenging it can be to cultivate gratitude during flare-ups. When caught in the grip of intense pain that lasts for hours, days, weeks, or even longer, it feels nearly impossible to foster a sense of thankfulness. Yet, I’ve discovered that embracing gratitude can be a crucial aspect of coping with chronic illness over the long haul.
Expressing Gratitude in Coping with Chronic Pain
Daily expressions of gratitude can be a powerful tool for managing chronic pain, offering both emotional and psychological benefits. When individuals take the time to acknowledge and appreciate the positive aspects of their lives, they effectively shift their focus away from pain and discomfort. This shift can create a sense of balance, allowing for moments of joy and contentment to emerge even amidst the challenges posed by chronic conditions.
Fostering a Positive Mindset
Gratitude encourages a positive mindset, which can significantly influence how we perceive and react to pain. By actively recognizing the things we are thankful for—be it supportive relationships, small victories, or moments of beauty in our daily lives—we create a mental buffer against negativity. This approach can lessen the impact of chronic pain symptoms and foster resilience, enabling us to navigate our circumstances with greater strength.
Enhancing Emotional Well-being
Chronic pain often comes with emotional burdens, such as frustration, sadness, and isolation. Practicing gratitude can counter these feelings by anchoring us in a place of appreciation and hope. Frequent acknowledgment of what we are grateful for helps to rewire our internal dialogue, promoting feelings of empowerment and control over our life experience. This emotional shift can lead to reduced anxiety and an overall enhanced sense of well-being.
Building Connections
Photo by Thirdman on Pexels.comExpressing gratitude can also strengthen social connections. When we share our gratitude with others, we open up opportunities for connection and support. This network can be vital for individuals dealing with chronic pain, as it fosters a sense of belonging and understanding. Engaging with empathetic friends, family, or support groups can enrich our coping strategies and provide avenues for sharing experiences and feelings.
Cultivating Mindfulness
Incorporating gratitude into our daily routine encourages mindfulness, prompting us to be present in the moment. This practice allows us to observe our thoughts and feelings about pain without judgment. By integrating gratitude moments into mindfulness exercises, we can deepen our awareness of both our pain and our capacity for joy, creating a holistic approach to managing chronic pain.
Developing Resilience
Photo by Andrea Piacquadio on Pexels.comFinally, gratitude cultivates resilience. By focusing on the positive aspects of our lives, we can better adapt to the challenges posed by chronic pain. This resilient mindset not only helps us endure difficult moments but also empowers us to explore solutions and treatments that enhance our quality of life. Embracing gratitude invites us to see beyond our present struggles and fosters hope for healing and growth.
Daily expressions of gratitude are a transformative practice for coping with chronic pain. By fostering a positive mindset, enhancing emotional well-being, building connections, cultivating mindfulness, and developing resilience, we can navigate our journey with greater clarity and strength, ultimately leading to a more fulfilling life.
https://open.spotify.com/episode/0aAbwS4h06BaL9GSyYlaQk?si=AdV1LU1yRh6bZ-18fzWp_A
Discover the beauty of resilience as you immerse yourself in this soothing guided meditation, thoughtfully designed to ease the physical and emotional burdens of chronic pain. Carry this sense of calm with you throughout your day, reminding yourself that you possess the inner strength and tools necessary to manage your pain. Thank you for dedicating this precious time to yourself.
Namaste.
#affirmation #awareness #balance #blessed #chronicIllness #chronicPain #chronicPainManagement #chronicPainRelief #emotionalWellness #experience #fibromyalgia #flow #gratitude #healing #health #holistic #holisticHealth #illness #lupus #managingPain #meditation #mentalHealth #mentalWellbeing #mentalWellness #mindful #moments #ms #pain #practice #spoonie #visualization
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City of Raleigh Government Event Guide – Tuesday April 28th Edition
Stay informed and engaged with what’s happening across the City of Raleigh. From planning discussions to public art conversations, here’s your DoRaleigh City of Raleigh Government Event Guide for Tuesday, April 28, 2026.
The DoRaleigh daily guide highlights key meetings, cancellations, and opportunities for residents to stay connected with local government.
🏛️ Tuesday, April 28, 2026 – Raleigh Government Meetings
🗂️ Planning Commission
🕘 9:00 AM
📍 Boards and Commissions
The Planning Commission reviews development proposals, zoning cases, and long-term growth strategies shaping Raleigh’s future.💧 In-Person Water Billing Help Session
🕙 10:00 AM
📍 Garner Senior Center
Residents can receive assistance with water bills, account questions, and payment options during this in-person help session.⚠️ Cancelled Meetings (City Council Committees)
The following committee meetings have been cancelled for today:
- ❌ Community Safety and Quality of Life Committee
🕦 11:30 AM - ❌ Economic Development and Innovation Committee
🕜 1:30 PM - ❌ Housing and Environment Committee
🕓 4:00 PM
These committees typically address major topics like public safety, economic growth, housing affordability, and environmental policy.
🎨 Public Art and Design Board Meeting
🕔 5:00 PM
📍 Boards and Commissions
🔗 Virtual meeting option availableThe Public Art and Design Board focuses on Raleigh’s public art initiatives, cultural investments, and design standards that enhance the city’s visual identity and community spaces.
📌 Why It Matters
These meetings play a critical role in shaping Raleigh’s future—from housing and infrastructure to arts and innovation. Staying informed gives residents a voice in local decision-making and helps strengthen community engagement.
🔗 How to Participate
- Attend meetings in person when available
- Join virtual sessions (links typically provided by the City)
- Review agendas and materials ahead of time
- Share public comments when applicable
⚠️ Know Before You Go
Meeting times, locations, and statuses can change. Always verify details through official City of Raleigh channels before attending.
Follow DoRaleigh.com for daily updates on government meetings, local festivals, and community happenings — your one-stop guide to everything Raleigh!
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#CityOfRaleigh #CityOfRaleighGovernmentEventGuide #CivicEngagementRaleigh #DoRaleigh #events #localGovernmentRaleigh #News #raleigh #RaleighBoardsAndCommissions #RaleighCityCouncil #RaleighGovernment #RaleighNCMeetings #RaleighPlanningCommission #RaleighPublicArt - ❌ Community Safety and Quality of Life Committee
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The Android Show 2026: Android 17 – oto co Google przygotowało dla twórców
Dla wielu twórców smartfon to główne narzędzie pracy – od uchwycenia momentu, przez montaż, aż po interakcję z fanami. Teraz Google obiecuje, że ma być łatwiej.
Android 17 wprowadza pakiet aktualizacji, które mają sprawić, że zamiast walczyć z ograniczeniami technologicznymi, będziemy mogli skupić się na samej kreatywności.
Screen Reactions: reakcje bez zielonego ekranu
Tworzenie popularnych „reakcji” na trendy czy komentarze staje się banalnie proste. Dzięki funkcji Screen Reactions wystarczy kilka tapnięć, aby jednocześnie nagrywać siebie i to, co dzieje się na ekranie telefonu. Twoja twarz zostanie automatycznie nałożona na wyświetlaną treść, eliminując potrzebę korzystania z zewnętrznych aplikacji czy ustawiania green screena.
Funkcja zadebiutuje na urządzeniach Pixel już tego lata.
Instagram Pro: koniec z „gorszą jakością” na Androidzie
Google połączyło siły z Meta, aby raz na zawsze rozwiązać problem jakości wideo w mediach społecznościowych. Na najbardziej zaawansowanych flagowcach z Androidem zadebiutuje w pełni zoptymalizowany Instagram:
- Ultra HDR: rejestracja i odtwarzanie treści z niespotykaną dotąd dynamiką kolorów.
- Wbudowana stabilizacja: płynne ujęcia nawet podczas tańca czy dynamicznego spaceru.
- Integracja Night Sight: doskonała jakość relacji nawet w najciemniejszych klubach czy przy nocnym oświetleniu miasta.
Co więcej, Google twierdzi, że dzięki całkowitej optymalizacji procesu od nagrania do publikacji, wideo z flagowych Androidów wypada w testach jakości UVQ (Universal Video Quality) tak samo lub lepiej niż u „głównego konkurenta”.
Edits: sztuczna inteligencja w służbie montażu
Ekskluzywnie na Androida trafi nowa wersja aplikacji Edits, która wykorzystuje AI do błyskawicznego „szlifowania” surowych nagrań.
- Smart enhance: jedno dotknięcie wystarczy, aby systemowo podnieść rozdzielczość i jakość zdjęć oraz filmów przy użyciu zaawansowanych algorytmów on-device.
- Sound separation: to koniec problemów z szumem wiatru czy przejeżdżającym autem w tle. Aplikacja automatycznie zidentyfikuje i odseparuje ścieżki audio, pozwalając Ci wyciszyć hałas i wzmocnić czystość głosu.
APV i Adobe Premiere: mobilna stacja robocza
Android staje się prawdziwą alternatywą dla komputera w pracy filmowca. Adobe Premiere trafi na Androida latem tego roku, oferując ekskluzywne szablony i efekty stworzone specjalnie pod format YouTube Shorts.
Wdrażany jest też standard APV (Advanced Professional Video). To nowy, najbardziej wydajny pod kątem zajmowanego miejsca format wideo dla profesjonalistów. Opracowany wspólnie z Samsungiem, jest już dostępny na Galaxy S26 Ultra oraz vivo X300 Ultra.
Na koniec podkreślono optymalizację Instagrama dla tabletów. Instagram otrzymał w końcu pełną optymalizację pod duże ekrany tabletów z Androidem, ułatwiając precyzyjną edycję treści i zarządzanie komentarzami.
#AdobePremiereAndroid #Android17 #formatAPV #GoogleIO2026 #iMagazineTech #InstagramPro #mobilneWideo #SamsungGalaxyS26Ultra #ScreenReactionsMeta wycofuje szyfrowane czaty na Instagramie. Opcjonalna funkcja zniknie w maju