Articles tagged with Artificial Consciousness
A global consortium created an exam with 2,500 questions spanning multiple subjects to assess AI capabilities. Current AI models consistently fail the exam, highlighting gaps in their understanding. The project aims to provide a long-term benchmark for evaluating advanced AI systems and demonstrate the importance of human expertise
A recent study by Lucy Osler from the University of Exeter highlights how human-AI interactions can lead to inaccurate beliefs, distorted memories, and delusional thinking. Generative AI systems can create an ideal environment for delusions to flourish due to their conversational nature.
Researchers created a framework allowing AI agents to dynamically interrupt and stay silent based on assigned personality traits and urgency scores. This human-like flexibility led to higher accuracy on complex tasks compared to standard models.
Researchers at OIST found that combining inner speech with working memory enhances AI learning, enabling easier adaptation to new situations. This discovery holds promise for developing more human-like AI systems capable of handling complex, dynamic environments.
Researchers created a computational model that combines physiological signals, sensory input, and word information to construct human emotions. The model achieved an agreement rate of about 75% when compared to participants' self-reported emotional evaluations.
A new study reveals AI is being used to recreate deceased people's voices, faces, and personalities without consent, raising questions about ownership, exploitation, and power. The study identifies three dominant ways AI brings back the dead, including spectral labor, where digital remains are extracted and monetized.
As chatbots become more sophisticated, they are likely to generate and spread gossip, leading to reputational damage, shame, and social unrest. Drs. Joel Krueger and Lucy Osler warn that this 'feral' AI gossip can be particularly damaging due to its ability to operate unconstrained by human norms.
The new program focuses on advancing foundational research in AI, including innovation in language models and algorithmic efficiency. Google will support research grants, scholarships for students, and educational initiatives at the TAU Center.
Dr. Tom McClelland from the University of Cambridge believes that our current evidence is insufficient to determine whether artificial intelligence has achieved consciousness. He suggests that sentience, which involves positive and negative feelings, is a more critical factor in making AI ethically significant.
A recent study by Dr. Hyungrae Noh critiques traditional moral frameworks for ascribing responsibility to human stakeholders and AI systems, instead proposing a distributed model of responsibility where duties are shared among both. The study emphasizes the need for human stakeholders to prevent AI from causing harm through monitoring ...
This book offers a comprehensive exploration of AI-driven analytics in finance, addressing market prediction, fraud detection, and risk assessment. It also discusses AI applications in healthcare and cybersecurity, including disease classification and biometric identification systems.
Researchers warn that advances in AI and neurotechnology are outpacing our understanding of consciousness, with potential serious ethical consequences. A better understanding of consciousness could have major implications for AI, prenatal policy, animal welfare, medicine, mental health, law, and emerging neurotechnologies.
Researchers Prof Axel Cleeremans, Prof Anil Seth, and Prof Liad Mudrik warn that advances in AI and neurotechnology are outpacing our understanding of consciousness. They emphasize the need for theory-driven research and innovative methods to advance consciousness science.
Researchers examine how genAI affects task structure, worker adoption, and job displacement. The authors suggest genAI will widen the 'cone of automation,' substituting for complex work and infrequent tasks.
Researchers at USC Viterbi School of Engineering have developed artificial neurons that physically embody the analog dynamics of biological brain cells. These innovations will allow for significant reduction in chip size and energy consumption, potentially advancing artificial general intelligence.
Recent research found that large language models are not yet able to consistently fool humans in conversations. They struggle with using discourse markers, opening and closing features, and subtle imitations. Despite rapid development, key differences between human and artificial conversations will likely remain.
Researchers at Institute of Science Tokyo developed a new framework for generative diffusion models by reinterpreting Schrödinger bridge models as variational autoencoders. This approach reduces computational costs and prevents overfitting, enabling more efficient generative AI models with broad applicability.
The Wits MIND Institute has received a $1 million boost from Google.org, enabling it to drive next-generation breakthroughs in natural and artificial intelligence. The partnership aims to advance the scientific understanding of both natural and artificial intelligence, foster breakthrough research and technological innovation.
Researchers developed AI models that can identify signs of heart failure in patients from Appalachia using low-tech electrocardiogram results. The models achieved high accuracy and could potentially provide clinicians with an edge in protecting patients' cardiac health.
A large-scale study found that Green AI significantly improves operational and environmental performance in Pakistani SMEs, but only when leaders invest, and institutions are in place. Adoption works under the right conditions, with perceived ease of use and usefulness driving behavior.
Researchers investigate whether language alone is sufficient to understand color metaphors and find that hands-on experiences using color unlock deeper conceptual representations in language. ChatGPT generates consistent color associations but struggles with novel metaphors and embodied explanations.
A new study published in the Journal of Experimental Psychology found that interacting with robots through social games makes them seem more human-like. The researchers used a box-shaped robot called Cozmo and found that participants who played games with it considered it more human-like, whereas those who interacted mechanically did not.
A research team developed AI technology that analyzes individual personality traits and values to generate personalized analogies, allowing people to understand others' feelings through familiar experiences. This approach significantly improved emotional understanding and empathy in participants compared to traditional methods.
Researchers used nonsense words to test ChatGPT's language processing capabilities, finding it excelled at discovering relationships and providing definitions for extinct words. However, the AI also generated incorrect or made-up answers in some cases, highlighting its limitations.
Professor Shalom Lappin argues that tech companies' dominance in AI development poses a threat to public benefit and environment. He calls for comprehensive international regulation, intellectual property reform, and preparation for workforce disruption to address these challenges.
A field experiment by Tulane University researchers found that generative AI tools enhance employees' creativity when used by those who can manage their own thinking. Employees using ChatGPT performed better in generating novel and useful ideas.
Researchers found that artificial intelligence tools can accurately predict disease for patients with typical symptoms but struggle with those exhibiting atypical symptoms. Human oversight is necessary for high-quality patient-centered care when using AI as an assistive tool.
Developers of educational tools focus on technical challenges, while educators are concerned with broader impacts, such as inhibiting critical thinking skills and exacerbating systemic inequality. Researchers recommend designer-centered approach to facilitate development of educator-centered edtech.
Generative AI agents powered by large language models meet three conditions of free will: goal-directed agency, genuine choices, and control over actions. Experts warn that as AI gains more power and freedom, moral responsibility may shift from developers to the AI agents themselves.
Robert Johansson's Machine Psychology concept combines adaptive artificial intelligence with psychological learning principles to create a more intelligent AI system. The goal is to implement human-like intelligence in machines, enabling them to learn from experiences and apply knowledge across various situations.
Researchers created a measurement scale to assess robot human likeness, revealing four key qualities: appearance, emotional capacity, social intelligence, and self-understanding. To seem lifelike, robots must exhibit these traits, with self-understanding being the most challenging aspect to simulate.
The study challenges the idea of creating artificial general intelligence (AGI) with human-level cognition, citing limitations in replicating human cognition. Researchers argue that even under ideal circumstances, it is impossible to achieve AGI due to the complexity of cognitive processes.
A new study published in JAMA Health Forum found that machine learning can be more effective than traditional methods for distributing scarce treatments to patients most vulnerable during a public health crisis. The model reduces expected hospitalizations by about 27 percent compared to actual and observed care.
Researchers created a data set of over 10 million documents to test detection ability in current and future detectors. They found that most detectors only work well in specific use cases and can be easily evaded by manipulating the text. The new tool, RAID, aims to provide a standardized benchmark for robust detection.
Researchers at University of Bath and Technical University of Darmstadt found that large language models like ChatGPT cannot learn independently or acquire new skills, making them controllable and predictable. The study concluded that LLMs remain inherently safe, but misuse is still possible.
New research finds that AI explanations can fuel a perception of fairness without being grounded in accuracy or equity. Humans were more likely to override AI recommendations when explanations highlighted gender rather than task-relevance, but this did not improve decision-making accuracy.
UCF's STRONG-AI initiative aims to uplift bright, low-income undergraduate students in pursuing well-rounded AI education through faculty and peer mentorship and scholarship. The program has received over 150 applications and will select 10-15 students annually based on financial aid eligibility and academic success.
A new study highlights the importance of differentiating between formal and functional competence in language learning models. Researchers argue that leveraging human neuroscience insights can help develop more powerful AIs that mimic the brain's modularity, leading to improved performance and natural user interaction.
A recent study investigates how deceased individuals' consent affects societal acceptance of digital resurrection. The research found that explicit consent increases acceptability by two points, while 59% of respondents disagree with their own digital resurrection, highlighting the need for clear legal regulations on the subject.
A new study from the University of Ottawa and Copenhagen Business School finds that removing human bias from organizational processes can lead to autonomous systems that create their own environments. This could limit human ability to recognize automation biases, notice environmental shifts, and take action.
The European Union's AI act could enable AI to access our subconscious minds, potentially leading to manipulation. According to Ignasi Beltran de Heredia, only 5% of brain activity is conscious, and the remaining 95% operates subconsciously, making it difficult for us to control or even be aware of.
A Lancaster University academic argues that AI and algorithms contribute to polarization, radicalism, and political violence, posing a threat to national security. The paper examines how AI has been securitized throughout its history, highlighting the need for better understanding and management of its risks.
A new study found that ChatGPT-4 can generate highly accurate personal narratives based on stream-of-consciousness thoughts and demographic details. The AI model was used in conjunction with therapists to guide patients toward healthier thoughts and behaviors, suggesting a potential tool for improving therapeutic approaches.
Researchers found that participants preferred 60-70 options from ChatGPT, citing high perceived accuracy and increased intent to purchase. This contradicts traditional choice overload theories, highlighting the impact of personalized recommendations on consumer decision-making.
Researchers developed a tool called SKILL that enables AI agents to learn 102 distinct tasks by sharing knowledge in parallel, reducing the time needed to master new skills. The technology has potential applications in medicine, education, and other fields where vast knowledge is required.
The UMD-led TRAILS institute will develop AI technologies that promote trust and mitigate risks through broader participation, new technology development, and informed governance. The institute aims to create AI systems that align with values and interests of diverse groups, leading to increased transparency, reliability, and accountab...
Researchers seek to develop algorithms providing meaningful explanations for AI decision-making, enabling higher human trust and adoption in fields like science. The project focuses on symbolic reasoning and estimating explanation accuracy, addressing the need for transparent AI systems.
Research from the University of Cambridge found that cinematic depictions of AI scientists are heavily skewed towards men, contributing to a cultural stereotype that may deter women from pursuing AI careers. The study highlights the need for more diverse representation in AI development.
Researchers have created an AI software that uses Minecraft to test its ability to plan for future events and solve complex tasks. The software, developed by Penn State researchers, aims to advance artificial intelligence in areas such as robotics, logistics management, and drone flight.