Ai Design Corps™ ’s Post

🌌 AI Fact of the Day: Unraveling the Mystery of AI Hallucinations! 🌌 Hallucinations can have real-world implications, affecting everything from medical diagnosis to judicial decision-making systems, emphasizing the importance of accuracy & reliability https://bit.ly/3Rcfamg

🌌 AI Fact of the Day: Unraveling the Mystery of AI Hallucinations! 🌌 Hallucinations can have real-world implications, affecting everything from medical diagnosis to judicial decision-making systems, emphasizing the importance of accuracy & reliability https://bit.ly/3Rcfamg

🌌 AI Fact of the Day: Unraveling the Mystery of AI Hallucinations! 🌌 Hallucinations can have real-world implications, affecting everything from medical diagnosis to judicial decision-making systems, emphasizing the importance of accuracy & reliability https://bit.ly/3Rcfamg

There is an extreme amount of negative propaganda regarding AI and hallucination; however, we rarely take the time to discuss blatant fraud on the part of humans and we fail to see how that affects the results given by AI models. Here we have a set of instances where humans either intentionally or unintentionally acted in a fraudulent manner. However, it is so pervasive, only AI could identify it at the scale it was really occurring. If you want an example of hallucination by humans, just look at the color purple because true purple doesn't exist. It's not even on the visible color spectrum and doesn't occur naturally. We only see purple when we trick our eyes into processing red and blue at equal levels.

For anyone interested, this is the PowerPoint I presented at the student-led seminar. I delve into the parallels between AI risk categorization and medical device classifications. Additionally, I emphasise the significance of recognising different categories of bias and fairness in AI.

With regard to Ethical AI. The Physicians paper work is where science of the profession converge with observation. Not only in convey of diagnoses. What's more about medical paperwork, there are indicators into the physicians mind

Predictive AI is used across multiple industries to perform tasks such as diagnosing patients, analyzing financial data, and aiding in police investigations. Despite the proliferation of these systems, they present ethical concerns around accuracy, transparency, and accountability. Learn more about predictive AI by exploring our key term page: https://lnkd.in/gHxnAeZ5

Viewpoint: The end of physicians?: As we enter the mid-2020s, we find ourselves at a crossroads. Artificial intelligence is becoming more and more common, and its abilities are expanding at an exciting (or alarming, depending upon your point of view) rate. Soon, we will turn AI loose, and armed with hundreds of millions of patient charts to learn from, it will effortlessly out-diagnose and out-treat every one of us.  http://dlvr.it/Sxzrjp

Imagine the scenery where an AI application to detect certain disease malfunctions, either cannot detect the presence of this disease or misdiagnoses the patient due to compromised data This is where ethical AI comes in. I was part of a conversation regarding this and thought to share on the importance of it

Artificial Stupidity: Anyone who thinks reviewing massive amounts of medical data to produce a useful AI program in medicine is a fool. Patients are misdiagnosed 40%-80% of the time, and doctors order the wrong tests 56%-77% of the time. Using these data will only produce GIGO. The concept is to use accurate data, not massive amounts of incorrect data. That is sort of like depending on a troop of monkeys with typewriters to produce a play by Shakespeare. See the attached publication.