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Plus, Meta uses your data to train AI

Workers Could Play Key Role in AI Regulation, Experts Suggest 

According to a report by the Financial Times, experts are suggesting that workers should take an active role in regulating AI. The report highlights concerns about AI potentially replacing jobs and the need for workers to have a say in its development and implementation. 

The experts argue that workers, who are directly affected by AI technologies, should be involved in shaping AI policies and regulations. This would ensure that AI is used in a way that benefits both businesses and workers. The report emphasizes the importance of workers’ perspectives and expertise in ensuring the responsible and ethical use of AI. It suggests that involving workers in AI regulation would lead to a fairer and more balanced approach to AI adoption in various industries.

The Impact of AI on Knowledge Work Revealed in New Study

A recent study conducted by Wharton Business School and the Boston Consulting Group (BCG) has revealed the positive impact of incorporating AI chatbots, such as ChatGPT, into knowledge work. Consultants who used AI outperformed those who did not, completing tasks more quickly, producing higher quality results, and finishing 12.2% more tasks on average. The study also found that AI acts as a skill-leveler, with lower-performing consultants experiencing the highest performance boost. 

These findings support previous research showing that AI improves productivity in various job roles. However, there are concerns that excessive reliance on AI could result in deskilling and a decline in human abilities. Organizations must strive to strike a balance between leveraging AI’s strengths and preserving human skills and judgment.

Meta AI Trains on Public Facebook and Instagram Posts, Raises Copyright Concerns

Meta, formerly known as Facebook, has revealed that it used publicly available Facebook and Instagram posts to train its AI models. The company’s president of global affairs, Nick Clegg, confirmed that the majority of the training data for its new AI assistants came from these public posts. However, Meta claims to have excluded datasets containing personal information from sources such as LinkedIn. 

This revelation has raised concerns among content creators who have been challenging tech companies’ use of their material in developing advanced AI tools. A legal battle is brewing between copyright holders and AI companies, as the latter may have inadvertently or intentionally used copyrighted content without permission. Meta argues that its use of posts for AI training falls under the legal doctrine of fair use, but it acknowledges that litigation may follow. Meanwhile, other platforms like Medium have blocked AI companies’ access to their content to use for training.

AI Identifies Brain Signals Associated With Recovery From Depression

AI has been utilized to identify brain signals linked to recovery from depression in a new study conducted by scientists in the US. The study involved 10 patients with treatment-resistant depression who underwent a six-month course of deep brain stimulation (DBS) therapy. DBS has yielded mixed results in the past, but the integration of AI has the potential to change that. Currently, the success of DBS relies on patients reporting their mood, which can be influenced by various factors. 

To address this, the researchers used electrode implants and AI analysis to pinpoint changes in brain activity patterns triggered by DBS. By identifying a biomarker for recovery from depression, the AI was able to provide accurate feedback on the effectiveness of the therapy. The AI’s training involved analyzing brain images taken before and after the treatment. This innovative approach could revolutionize the monitoring and tailoring of depression treatments in the future.

AI-Powered Fashion Forecasting Emerges as the New Trendsetter

As Paris Fashion Week draws attention to the latest designs, fashion forecasters armed with AI tools are busy identifying emerging trends. Traditionally, these trend forecasters relied on observing runway shows and pop culture to make predictions for designers and retailers. However, with the rise of powerful AI technologies, forecasting agencies are turning to machine learning algorithms to analyze large datasets of images, social media posts, search data, and sales figures. 

This enables them to detect patterns and forecast trends more accurately and quickly. Accurate trend forecasts not only impact the financial bottom line of fashion companies but also have implications for reducing waste and making the industry more sustainable. However, while AI tools offer valuable insights, human creativity and the ability to interpret broader social and cultural contexts remain crucial in fashion forecasting.

AI-Tech Leads To NASA Energy Breakthrough

NASA and ADC Energy USA have released groundbreaking research on a new energy technology called alternating direct current (ADC). ADC, enabled by AI, eliminates the need for conventional AC/DC power conversion, allowing for lossless power transmission. The joint research paper validates ADC as a “hybrid” form of energy that can operate on the same wires as AC and DC, revolutionizing global energy and climate solutions. The technology has applications in low voltage, quick EV charging, solar panel generation, and off-grid indoor agriculture. 

The research also highlights recent advancements in room temperature superconductivity, which could make power transmission more efficient. Scientists at the University of Rochester created a superconducting material capable of operating at temperatures as high as 70 degrees Fahrenheit, opening up possibilities in transportation, energy storage, and medical imaging.

Generative AI Systems Could Solve Education’s 2 Sigma Problem

A new report suggests that generative AI systems could hold the key to solving the longstanding challenge known as Bloom’s 2 Sigma Problem in education. This problem refers to the fact that students who receive one-on-one tutoring perform significantly better than those in traditional classroom settings. Private tutoring is not feasible on a large scale, but AI systems have the potential to replicate some benefits of personalized instruction. 

These systems, such as OpenAI’s ChatGPT, can analyze complex data patterns and deliver personalized educational content to students. They can break down difficult topics into easier-to-understand information, making learning more accessible. AI has the power to level the playing field in education and provide high-quality, personalized learning for all students.




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