December 9, 2023

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"Sports wagering - a most fertile ground for IntualityAI", by Rich Ziskind, PhD 

"Resilience and Prediction", by Dr Howard Rankin

 "Set Reasoning in AI involves grouping data based on shared characteristics", by Grant Renier

Current Prediction News

— Historical Prediction Results —

Sports wagering - a most fertile ground for IntualityAI

The magnitude of sports wagering is enormous. Once localized to Sports Books in Nevada and unlawful bookie transactions. No more! Internet sites and a growing number of states allowing sports betting have fostered exponential growth in the U.S. as well as internationally. Television broadcasts sporting events with announcers and other talking heads providing information and analyses on the betting lines. Newspapers show match odds as do Internet handicapping and sports news sites. Numerous on- and- offshore betting sites are available along with brick and mortar facilities. 

Fantasy sports league competitions: have sprouted up drawing family members, co-workers, social groups etc. to vie for cash awards. Handicappers and betting opportunities abound, led by casino sponsored applications (Apps) enabling easy access both prior to and during competitions (‘In Game Wagering’) 

It is critical to appreciate: that the offered betting line odds established by such sites have an ironic goal---Establish the odds such that the site owners accepting the wagers are NOT GAMBLING. Ideally, they establish, adjust and maintain the lines such that they create the right balance among their customer betting pool such that they win no matter the outcome. 

Here's where we step in through our prediction methodology. We apply IntualityAI to derive the ‘true’ odds/point spreads. We factor in expected performance and MOST IMPORTANTLY account for human biases that drive the odds from an optimal performance-based prediction. 

It incorporate the effects of 12 Cognitive Biases: recognized as influencing human behavior---most importantly what drives human decision making. These literally go from A (Anchoring Bias) to Z (Zero Risk Bias). For more insight do a Google search, such as, ’12 Cognitive Biases That Affect How We Make Everyday Decisions.’ 

We have demonstrated that considering human biases: create profitable betting opportunities. Simply put, IntualityAI contrasts predicted point spreads for NFL football games with available lines from wagering sites and make wagers and/or recommendations to/for interested parties. Results over 9 years are presented in the figure below showing a 60 percent (%) win rate and a strong ROI. Note a win rate of 52.4% is considered ‘break even’ as derived through wagering at typical sites and casinos. Since casino table games e.g. blackjack and dice operate with about a 3% edge for the ‘house,’ and that edge is the basis for the construction and operation of mega resort/casinos, picture the value of a 7% plus edge!! 

In subsequent articles we will talk to the non-proprietary details: of the IntualityAI sports wagering approach to exploit these opportunities for profit through quantitative implementation of our analyses of the 12 Cognitive Biases. Please review the performance results of the 9 years (2011-2020) that are based upon AI analyses augmented by the principles of human behavior. Data files/results for 2021, 2022 and 2023 to-date are currently being prepared. 

by Rich Ziskind PhD, CEO IntualitySports, nuclear engineering and physics, business founder, professional poker player

Resilience and Prediction

The term “resilience” is used in psychology: to characterize a trait in which people are adaptive and capable of managing varying situations and stressors. The term typically entails other characteristics such as emotional regulation, problem-solving, a positive mindset, the ability to learn from any experience, the ability to develop coping strategies. Resilience is also associated with good levels of social support and investment in physical well-being. Resilience is the key to success in anything but especially when trying to change self-destructive behaviors and managing challenging situations like a cancer diagnosis.

Developing strategies: to teach people resilience is also a goal of several people within healthcare systems who appreciate the importance of it in post-diagnosis adaptation, recovery and even survival.

While measuring someone’s general resilience: can be helpful, measuring and predicting levels of resilience in the moment or in the immediate future offers even more value. In this case rather than being a general characteristic, a measure of resilience now and in the next few minutes would be very helpful in guiding behavior in the present, leading to better actual outcomes rather than probabilities. Not only could such a measurement guide more adaptive behavior, it could also make users more aware of the need to check their vulnerability in any situation.

In a recent study (Perna et al., 2019) the authors write…

“Usually, measurement of resilience is based on subjective reports, susceptible to biases. It justifies the need for objective biological/physiological biomarkers of resilience. One promising candidate as biomarker of mental health resilience (MHR) is heart rate variability (HRV).”

In another study (An et al., 2020), twenty-four male participants from the Army National Guard Special Forces completed psychological measures known to relate to resilience and had HRV measured while undergoing stressful virtual environment scenarios. The authors concluded that…

“HRV appears to represent some aspects of an individual's overall resilience profile. Although resilience remains a complex, multidimensional construct, HRV shows promise as a global psychophysiological index of resilience.”

The core issue for millions of people: trying to change habits is the ability to resist temptation which revolves around two strategies: avoidance and confrontation. The ability to confront temptation and resist engaging in old habits is the key to real, maintainable behavior change. That is where the underlying neural infrastructure gets broken down making it less automatic and allowing conscious control to be implemented.

In an early study, my colleagues and I at the Institute of Psychiatry Addiction Research Unit: showed that controlled exposure to alcoholics resulted in a subsequent reduction of temptation. The issue for most addicts is the sense that they have no control and therefore avoidance is their main strategy. This can be helpful initially, but it can also reinforce both the idea and underlying physiology that if you find yourself in a tempting situation, you won’t be able to cope.

What our studies at the Addiction Research Unit and my work: with addicts of all sorts over the years show, is that for sustainable recovery you have to be able to confront temptation and manage behavior. The problem with this and any other potentially stressful situation is that one’s ability to prevail over tempting cues varies based on your current psychophysiological state and the intensity of the temptation.

With the advent of wearable devices: providing real time information about aspects of one’s state of resilience, it would be now possible to predict the probability of someone successfully confronting temptation and provide alerts accordingly. For example, biometrics like heart rate variability measures run through IntualityAI, would be able to predict the probability of a person resisting a specific temptation, thus encouraging them to confront or avoid.

In addition to this application: specific to behavior change, the same measures could predict a person’s ability to deal with a stressful situation, thus encouraging them to either right now deal with the situation or avoid it for a certain time frame.

by Howard Rankin PhD, Intuality Science Director, psychology and cognitive neuroscience

Set Reasoning in AI involves grouping data into sets based on shared characteristics

IntualityAI employs set reasoning: as a crucial mechanism in its decision-making process. Set reasoning in AI refers to making inferences and decisions based on analyzing sets of data, particularly effective in complex, uncertain, or ambiguous situations. The system applies a correlation process to its constantly evolving landscape of future probabilities of all inputs.  The result is stronger regional sub-sets of future probabilities that mix objective and influencer information. For example, prediction of the next NFL play is 'enriched' by similar play results (objective data) and the temperature on the field (influencer data). 

Understanding Set Reasoning: in AI involves grouping data into sets based on shared characteristics and applying logical rules to these sets for conclusions or predictions. It’s especially useful in AI for handling diverse and complex data.

Data Grouping and Classification: begins by processing vast data, categorizing it into sets based on IntualityAI's correlation function. For example, in healthcare, patient data might be grouped by symptoms or demographics.

Pattern Recognition: is pattern recognition within data sets. IntualityAI identifies commonalities or trends within these groups, which is crucial for making predictions. In financial applications, this could mean spotting trends in predicted probabilities to forecast future movements.

Probabilistic Reasoning: in IntualityAI involves assessing the likelihood of outcomes based on probabilities within data sets. This approach is beneficial in scenarios with incomplete or uncertain data, allowing the AI to make informed predictions.

Decision Making: IntualityAI uses the insights from set analysis to make decisions and output actionable alerts. This facilitates complex decision-making that encompasses a broad range of factors.

Learning and Adaptation: IntualityAI learns and adapts with each new event of data inputs.  It reevaluates and adjusts its sets, leading to the emergence of new patterns or changes in probabilities. This machine learning aspect enhances the system's accuracy and effectiveness.

Application Across Fields: versatility of set reasoning allows IntualityAI’s application across many sectors. In healthcare, it can predict patient health events that could  lead to effective treatments. In finance, it's used for market trend forecasting and risk assessment. This adaptability is due to its proficiency in managing diverse data sets within its terrain of all future probabilities.

Advantages and Challenges: of set reasoning in IntualityAI is its ability to handle complex and uncertain information flexibly and robustly. 

IntualityAI’s incorporation of set reasoning: marks a significant advancement in pursuing general artificial intelligence. By analyzing and applying complex correlations to data sets, IntualityAI can make informed decisions in uncertain environments. This method is both powerful and adaptable. As the IntualityAI evolves, its decision-making accuracy is expected to improve further, highlighting the potential and importance of set reasoning in artificial intelligence.

by Grant Renier, Intuality Chairman, engineering, mathematics, behavioral science, economics

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