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Tech chiefs call on scientists to pause development of AI systems.

Technology experts, including Elon Musk, have urged scientists to pause developing artificial intelligence to ensure it does not pose a risk to humanity. Tech chiefs including Apple co-founder Steve Wozniak and Skype co-founder Jaan Tallinn have signed an open letter demanding all labs stop training AI systems for at least six months.
The letter said: “Recent months have seen AI labs locked in an out-of-control race to develop and deploy ever more powerful digital minds that no one – not even their creators – can understand, predict, or reliably control. Contemporary AI systems are now becoming human-competitive at general tasks, and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth?” It added: “Powerful AI systems should be developed only once we are confident that their effects will be positive, and their risks will be manageable.” The technology chiefs do not want any AI systems more powerful than new chatbot GPT-4 and called for researchers to focus on making sure the technology is accurate, safe, and transparent.
US tech firm OpenAI has just released its latest version of AI chatbot ChatGPT. It was launched late last year, and it has become an online sensation because of its ability to hold natural conversations and to generate speeches, songs, and essays. The bot can respond to questions in a human-like manner and understand the context of follow-up queries, much like in human conversations. It can even admit its own mistakes or reject inappropriate requests. According to OpenAI, GPT-4 has “more advanced reasoning skills” than ChatGPT but, like its predecessors, GPT-4 is still not fully reliable and may “hallucinate” – a phenomenon where AI invents facts or makes reasoning errors.
The letter said humanity can now enjoy an “AI summer” where it can reap the rewards of the systems but only once safety protocols have been made. It added “Humanity can enjoy a flourishing future with AI. Having succeeded in creating powerful AI systems, we can now enjoy an ‘AI summer’ in which we reap the rewards, engineer these systems for the clear benefit of all and give society a chance to adapt. Society has hit pause on other technologies with potentially catastrophic effects on society. We can do so here. Let’s enjoy a long AI summer, not rush unprepared into a fall.”

(From: https://www.independent.co.uk/tech Access: 04/11/2023. Adapted.)

TEXTO

HOW ARTIFICIAL INTELLIGENCE IS POISED TO RESHAPE MEDICINE

In a recent review published in the journal of Nature Medicine, scientists discuss the results of a two-year
weekly effort to track and communicate significant developments in medical AI (Artificial Intelligence).
They include prospective studies as well as developments in medical image analysis that have narrowed
the gap between research and implementation. They also discuss non-image data sources, innovative issue
[5] formulations, and human-AI collaboration as prospective pathways for novel medical AI research.

Many randomized controlled trials (RCTs) have been used to assess the utility of AI systems in healthcare.
An RCT evaluating an AI system for managing insulin doses, for example, measured the time patients spent
within the target glucose range, and a study evaluating a monitoring system for intraoperative hypotension
tracked the average duration of hypotension episodes.

[10] AI has also made significant progress in pathology, mainly through the use of whole-slide imaging, in
identifying tumors and offering new disease insights. For example, in gastroenterology, deep learning
has made considerable progress, particularly in terms of enhancing colonoscopy, a vital test for detecting
colorectal cancer.

Despite the remarkable progress in AI, a few obstacles are associated with its widespread use. Although it is
[15] thought that AI will lower medical expenditures, the instruments required to gather data for AI systems can
be prohibitively expensive. Large image sizes raise additional difficulties as the amount of memory needed
for a neural network grows in tandem with the model’s complexity and the number of pixels in the input.

Adapted from: https://www.news-medical.net/news/20220124/How-artificial-intelligence-is-poised-to-reshape-medicine.aspx. Accessed April 10 2023. 

TEXTO

HOW ARTIFICIAL INTELLIGENCE IS POISED TO RESHAPE MEDICINE

In a recent review published in the journal of Nature Medicine, scientists discuss the results of a two-year
weekly effort to track and communicate significant developments in medical AI (Artificial Intelligence).
They include prospective studies as well as developments in medical image analysis that have narrowed
the gap between research and implementation. They also discuss non-image data sources, innovative issue
[5] formulations, and human-AI collaboration as prospective pathways for novel medical AI research.

Many randomized controlled trials (RCTs) have been used to assess the utility of AI systems in healthcare.
An RCT evaluating an AI system for managing insulin doses, for example, measured the time patients spent
within the target glucose range, and a study evaluating a monitoring system for intraoperative hypotension
tracked the average duration of hypotension episodes.

[10] AI has also made significant progress in pathology, mainly through the use of whole-slide imaging, in
identifying tumors and offering new disease insights. For example, in gastroenterology, deep learning
has made considerable progress, particularly in terms of enhancing colonoscopy, a vital test for detecting
colorectal cancer.

Despite the remarkable progress in AI, a few obstacles are associated with its widespread use. Although it is
[15] thought that AI will lower medical expenditures, the instruments required to gather data for AI systems can
be prohibitively expensive. Large image sizes raise additional difficulties as the amount of memory needed
for a neural network grows in tandem with the model’s complexity and the number of pixels in the input.

Adapted from: https://www.news-medical.net/news/20220124/How-artificial-intelligence-is-poised-to-reshape-medicine.aspx. Accessed April 10 2023. 

TEXTO

HOW ARTIFICIAL INTELLIGENCE IS POISED TO RESHAPE MEDICINE

In a recent review published in the journal of Nature Medicine, scientists discuss the results of a two-year
weekly effort to track and communicate significant developments in medical AI (Artificial Intelligence).
They include prospective studies as well as developments in medical image analysis that have narrowed
the gap between research and implementation. They also discuss non-image data sources, innovative issue
[5] formulations, and human-AI collaboration as prospective pathways for novel medical AI research.

Many randomized controlled trials (RCTs) have been used to assess the utility of AI systems in healthcare.
An RCT evaluating an AI system for managing insulin doses, for example, measured the time patients spent
within the target glucose range, and a study evaluating a monitoring system for intraoperative hypotension
tracked the average duration of hypotension episodes.

[10] AI has also made significant progress in pathology, mainly through the use of whole-slide imaging, in
identifying tumors and offering new disease insights. For example, in gastroenterology, deep learning
has made considerable progress, particularly in terms of enhancing colonoscopy, a vital test for detecting
colorectal cancer.

Despite the remarkable progress in AI, a few obstacles are associated with its widespread use. Although it is
[15] thought that AI will lower medical expenditures, the instruments required to gather data for AI systems can
be prohibitively expensive. Large image sizes raise additional difficulties as the amount of memory needed
for a neural network grows in tandem with the model’s complexity and the number of pixels in the input.

Adapted from: https://www.news-medical.net/news/20220124/How-artificial-intelligence-is-poised-to-reshape-medicine.aspx. Accessed April 10 2023. 

TEXTO

HOW ARTIFICIAL INTELLIGENCE IS POISED TO RESHAPE MEDICINE

In a recent review published in the journal of Nature Medicine, scientists discuss the results of a two-year
weekly effort to track and communicate significant developments in medical AI (Artificial Intelligence).
They include prospective studies as well as developments in medical image analysis that have narrowed
the gap between research and implementation. They also discuss non-image data sources, innovative issue
[5] formulations, and human-AI collaboration as prospective pathways for novel medical AI research.

Many randomized controlled trials (RCTs) have been used to assess the utility of AI systems in healthcare.
An RCT evaluating an AI system for managing insulin doses, for example, measured the time patients spent
within the target glucose range, and a study evaluating a monitoring system for intraoperative hypotension
tracked the average duration of hypotension episodes.

[10] AI has also made significant progress in pathology, mainly through the use of whole-slide imaging, in
identifying tumors and offering new disease insights. For example, in gastroenterology, deep learning
has made considerable progress, particularly in terms of enhancing colonoscopy, a vital test for detecting
colorectal cancer.

Despite the remarkable progress in AI, a few obstacles are associated with its widespread use. Although it is
[15] thought that AI will lower medical expenditures, the instruments required to gather data for AI systems can
be prohibitively expensive. Large image sizes raise additional difficulties as the amount of memory needed
for a neural network grows in tandem with the model’s complexity and the number of pixels in the input.

Adapted from: https://www.news-medical.net/news/20220124/How-artificial-intelligence-is-poised-to-reshape-medicine.aspx. Accessed April 10 2023. 

TEXTO

TELEMEDICINE WIDELY VIEWED AS AN EFFECTIVE MEANS FOR DELIVERING CARE

Reviewed by Emily Henderson, B.Sc.Jul 25 2022

After experiencing a rapid expansion early in the COVID-19 pandemic, a new survey indicates that
telemedicine is now widely viewed as an effective means for delivering care. In results published online on
June 15 in NEJM Catalyst Innovations in Care Delivery, a majority of respondents credited telemedicine with
improving patient health, providing good quality care and increasing access for vulnerable populations.
[5] However, the results also point to challenges that must be addressed as this field becomes more established.

According to the survey, 84 percent in the United States agreed that telemedicine increased access for
vulnerable populations – a result that reflects the ability of telemedicine to reach people who would
otherwise go without care, according to Dr. Sharma (professor and chair of emergency medicine at Weill
Cornell Medicine). Despite this encouraging statistic, disparities remain. Access to telemedicine – for reasons
[10] ranging from language barriers to lack of high-speed internet connection – ranked as the number one
challenge facing the field.

The results also highlighted other areas for improvement. While in-person care is evaluated using quality
metrics, such as rates of infections, these measures are much less common in telemedicine. Only 28
percent of U.S. respondents said their organizations currently apply quality metrics to telemedicine, while
[15] approximately 38 percent say their institution offers training on how to, for example, perform an exam
remotely.

“This global report demonstrates a clear need for telemedicine beyond the pandemic setting,” Dr. Sharma
said. “It also drives home that this modality, like any other in health care, must meet expectations of quality,
training and access, and standards of care. Essentially, this service cannot be an afterthought. It requires a
[20] comprehensive approach to get it right and to make a meaningful impact.”

Adapted from news-medical.net. Accessed August 22 2022.