MORAVEC’S A.I. PARADOX: In Healthcare

Posted on January 25, 2026 by Dr. David Edward Marcinko MBA MEd CMP™
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A paradox is a logically self-contradictory statement or a statement that runs contrary to one’s expectation. It is a statement that, despite apparently valid reasoning from true or apparently true premises, leads to a seemingly self-contradictory or a logically unacceptable conclusion. A paradox usually involves contradictory-yet-interrelated elements that exist simultaneously and persist over time. They result in “persistent contradiction between interdependent elements” leading to a lasting “unity of opposites”.

MORAVEC’S ARTIFICIAL INTELLIGENCE HEALTHCARE PARADOX

Classic Definition: Artificial intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems. The term “AI” describes a wide range of technologies that power many of the services and goods we use every day – from apps that recommend TV shows to chat-bots that provide customer support in real time.

Modern Circumstance: The role of artificial intelligence in health care is becoming an increasingly topical and controversial discussion. There remains uncertainty about what is achievable regarding ongoing medical artificial intelligence research. Although there are some people who believe that artificial intelligence will be used, at best, as a tool to assist clinicians in their day-to-day activities, there are others who believe that job automation and replacement is a looming threat.

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Social HMOs

Paradox Example: Moravec’s paradox is a phenomenon observed by robotics researcher Hans Moravec, in which tasks that are easy for humans to perform (eg, motor or social skills) are difficult for machines to replicate, whereas tasks that are difficult for humans (eg, performing mathematical calculations or large-scale data analysis) are relatively easy for machines to accomplish.

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For example, a computer-aided diagnostic system might be able to analyze large volumes of images quickly and accurately but might struggle to recognize clinical context or technical limitations that a human radiologist would easily identify.

Similarly, a machine learning algorithm might be able to predict a patient’s risk of a specific condition on the basis of their medical history and laboratory results but might not be able to account for the nuances of the patient’s individual case or consider the effect of social and environmental factors that a human physician would consider.

In surgery, there has been great progress in the field of robotics in health care when robotic elements are controlled by humans, but artificial intelligence-driven robotic technology has been much slower to develop.Thus far, research into clinical artificial intelligence has focused on improving diagnosis and predictive medicine.

Assessment

Moravec’s paradox also highlights the importance of maintaining a human element in the health-care system, and the need for collaboration between humans and technology to achieve the best possible outcomes.

Conclusion

In the field of medicine, it is becoming indisputable that artificial intelligence will have a role in population health analysis, predictive medicine, and personalized care.

However, for now, the job of doctors seems safe from automation.

Cite: Shuaib A: The increasing role of artificial intelligence in health care: will robots replace doctors in the future? Int J Gen Med. 2020; 13: 891-896

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MACD: Moving Average Convergence/Divergence

Posted on January 25, 2026 by Dr. David Edward Marcinko MBA MEd CMP™

DEFINITION

Staff Reporters

SPONSOR: http://www.MarcinkoAssociates.com

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From Wikipedia, the free encyclopedia

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Example of historical stock price data (top half) with the typical presentation of a MACD(12,26,9) indicator (bottom half). The blue line is the MACD series proper, the difference between the 12-day and 26-day EMAs of the price. The red line is the average or signal series, a 9-day EMA of the MACD series. The bar graph shows the divergence series, the difference of those two lines.

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MACD, short for moving average convergence/divergence, is a trading indicator used in technical analysis of securities prices, created by Gerald Appel in the late 1970s. It is designed to reveal changes in the strength, direction, momentum, and duration of a trend in a stock’s price.

The MACD indicator (or “oscillator”) is a collection of three time series calculated from historical price data, most often the closing price. These three series are: the MACD series proper, the “signal” or “average” series, and the “divergence” series which is the difference between the two. The MACD series is the difference between a “fast” (short period) exponential moving average (EMA), and a “slow” (longer period) EMA of the price series. The average series is an EMA of the MACD series itself.

The MACD indicator thus depends on three time parameters, namely the time constants of the three EMAs. The notation “MACD(a,b,c)” usually denotes the indicator where the MACD series is the difference of EMAs with characteristic times a and b, and the average series is an EMA of the MACD series with characteristic time c. These parameters are usually measured in days. The most commonly used values are 12, 26, and 9 days, that is, MACD (12,26,9). As true with most of the technical indicators, MACD also finds its period settings from the old days when technical analysis used to be mainly based on the daily charts. The reason was the lack of the modern trading platforms which show the changing prices every moment. As the working week used to be 6-days, the period settings of (12, 26, 9) represent 2 weeks, 1 month and one and a half week. Now when the trading weeks have only 5 days, possibilities of changing the period settings cannot be overruled. However, it is always better to stick to the period settings which are used by the majority of traders as the buying and selling decisions based on the standard settings further push the prices in that direction.

Although the MACD and average series are discrete values in nature, but they are customarily displayed as continuous lines in a plot whose horizontal axis is time, whereas the divergence is shown as a bar chart (often called a histogram).

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MACD indicator showing vertical lines (histogram)

A fast EMA responds more quickly than a slow EMA to recent changes in a stock’s price. By comparing EMAs of different periods, the MACD series can indicate changes in the trend of a stock. It is claimed that the divergence series can reveal subtle shifts in the stock’s trend.

Since the MACD is based on moving averages, it is a lagging indicator. As a future metric of price trends, the MACD is less useful for stocks that are not trending (trading in a range) or are trading with unpredictable price action. Hence the trends will already be completed or almost done by the time MACD shows the trend.

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QUANTUM MECHANICS: Unlocking the Secrets of the Microscopic Universe

Posted on January 25, 2026 by Dr. David Edward Marcinko MBA MEd CMP™

By Artificial Intelligence

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Quantum mechanics is a fundamental branch of physics that explores the behavior of matter and energy at the smallest scales—typically atomic and subatomic levels. Unlike classical physics, which deals with predictable and continuous phenomena, quantum mechanics reveals a world governed by probabilities, uncertainties, and strange dualities. It challenges our intuitive understanding of reality and has revolutionized both science and technology.

The origins of quantum mechanics trace back to the early 20th century, when classical theories failed to explain certain experimental results. Max Planck’s work on black-body radiation in 1900 introduced the idea that energy is quantized, meaning it comes in discrete packets called “quanta.” This concept laid the foundation for quantum theory. Soon after, Albert Einstein explained the photoelectric effect by proposing that light itself is made of particles—later called photons—further reinforcing the idea of quantization.

One of the most striking features of quantum mechanics is wave-particle duality. According to this principle, particles such as electrons and photons exhibit both wave-like and particle-like behavior depending on how they are observed. This duality was famously demonstrated in the double-slit experiment, where particles create an interference pattern typical of waves when not observed, but behave like particles when measured.

Another cornerstone of quantum mechanics is Heisenberg’s uncertainty principle, which states that certain pairs of physical properties—like position and momentum—cannot both be known precisely at the same time. This introduces a fundamental limit to measurement and implies that the act of observing a system can alter its state.

Quantum mechanics also introduces the concept of superposition, where particles can exist in multiple states simultaneously until measured. This idea is illustrated by Schrödinger’s cat thought experiment, in which a cat in a sealed box is both alive and dead until the box is opened and the cat is observed. Though metaphorical, this paradox highlights the non-intuitive nature of quantum systems.

Perhaps the most mysterious phenomenon in quantum mechanics is entanglement. When particles become entangled, their states are linked regardless of the distance between them. A change in one particle instantly affects the other, defying classical notions of locality. This “spooky action at a distance,” as Einstein called it, has been experimentally confirmed and is the basis for emerging technologies like quantum cryptography and quantum teleportation.

Quantum mechanics is not just theoretical—it has practical applications that shape our modern world. Technologies such as lasers, semiconductors, MRI machines, and atomic clocks all rely on quantum principles. Moreover, quantum computing promises to revolutionize information processing by using quantum bits (qubits) that can represent multiple states simultaneously, enabling calculations far beyond the reach of classical computers.

In conclusion, quantum mechanics is a profound and essential framework for understanding the universe at its most fundamental level. It challenges our perceptions, fuels technological innovation, and continues to inspire scientists and philosophers alike. As research advances, quantum mechanics may unlock even deeper mysteries of reality, reshaping our understanding of existence itself.

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