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Prediction AI Is On The Way. Is Everyone Prepared (Including You)?

Prediction AI Is On The Way. Is Everyone Prepared (Including You)?

Predictive AI/Prediction AI: What is it? Predictive artificial intelligence (AI) is the application of machine learning to discover trends in historical data and forecast future occurrences. AI can forecast the future and entire populations regarding events like political elections or economic trends. When it comes to making personal predictions, people are infamously terrible.

Prediction AI: What is it?

An example of AI is predictive programming, which can analyze data statistically to look for trends, predict how people will act, and foretell what will happen next. While statistics has always been a useful tool for foretelling the future, predictive AI uses machine learning and access to massive data sets to speed up and, in theory, improve the accuracy of statistical research. Even though it can’t promise accurate forecasts, predictive AI can help companies plan and provide customers with more tailored experiences.

Picture this: Joey is a fisherman who, before launching his boat, wants to know the forecast. Joey has been through a storm every time he wakes up to a red sky in the past three months. For some reason, Joey keeps thinking that a red sky is a sign that a storm is on the way. Similar results are obtained by predictive AI, but this time, it takes decades’ worth of data and thousands of variables (rather than simply the sky’s color) to arrive at its findings.

Among the several capabilities provided by artificial intelligence (AI), which is a collection of skills that computers can possess to mimic human cognition, is predictive AI.

Who here does not wonder what the future holds? How frequently do you imagine the short-term and long-term outcomes of your life? Are you worried about how long you have left to live, how successful your kids will be, or what your hard work at work will bring about? These introspective inquiries reveal our natural interest in the future.

Human life rests on the foundation of prediction. Living a life that makes sense requires anticipation of what’s to come. You need to be able to “guesstimate” the next stages in a chain of events in your life to plan for the future.

Because prediction is so important in daily life, you might not even know your insatiable curiosity about what lies ahead. Some people are more preoccupied with the future than others for reasonable or irrational reasons. But at least some of us are interested in the future, and that’s where a new AI product could find a huge audience.

The artificial intelligence sector seems hurtling towards an imminent future even while the exact launch date is still up in the air. If you find Generative AI (such as OpenSource’s ChatGPT or Google’s Gemini) impressive, get ready for a knowledgeable bot to inform you of your life’s predictions.

In Contrast To Predictive AI, Generative AI

Prediction AI

There are two main categories of AI, generative AI (GenAI) and predictive AI (PredAI), each with its own set of uses and goals.

Generative AI: GenAI takes its cues from a deep learning-based transformer model specializing in NLP. The GenAI model can simultaneously examine all input segments, including data scraped from the Internet. These big language models make rapid text analysis possible and prioritize relevant areas during output production.

Unlike typical AI systems that rely on established rules or patterns, GenAI is designed to “imagine” and develop content that was not expressly coded, be it writing, images, music, or even code, that is innovative and entertaining.

PredAI’s main focus is foretelling future events by analyzing patterns, trends, and historical data. This method employs data analytics, statistical models, and machine learning algorithms to forecast and advise.

For certain fields (e.g., healthcare, markets, sports, etc.), PredAI employs predictive analytics to assess a combination of current occurrences and historical data to generate informed predictions regarding future outcomes. Machine learning may sift through massive datasets, searching for patterns to augment predictive analytics. The accuracy of their forecasts is directly proportional to the amount and quality of data available for the areas of interest and the strength of the pattern history.

Will AI Be Able to Tailor Its Predictions to You?

Prediction AI

As you would have guessed from reading about PredAI, this model needs a mountain of data about the prediction domain’s past. Once you enter the prediction domain, the PredAI model will require copious amounts of personal data if you desire a customized version of PredAI to provide you with future predictions.

Why does PredAI require access to much past data to make accurate predictions? According to statistical probability, your future is defined by your habits. You are a creature of habit, and your habits interest Pred AI.

Tech journalist and futurist Patrick Tucker penned The Naked Future (2014) a decade ago. What Happens in a World That Anticipates Your Every Move? was the subtitle that piqued my interest in the book.

Tucker’s book elaborates upon a theory that many cognitive scientists are familiar with—that the human mind is a computer for making predictions. The essence of being human is constantly wondering what’s around the corner.

Making predictions isn’t just something the brain sometimes does; it’s an inherent quality that is always there and crucial to learning. Confirming the brain’s predictions indicates that the brain’s world model is correct. When you fix a mistake and update the model, it’s because of a misprediction.

According to Tucker, we determine how to handle the future by mentally representing the here and now. Based on our varied life experiences, we all have a plethora of preconceived notions and theories about the world around us.

Let me give you a basic example. One of the first things a kid learns is how to use utensils properly. Your brain then creates models for each of them. As an adult, you subconsciously borrow from those examples the next time you serve soup to visitors at the dinner table using spoons instead of forks.

In addition to physical objects, you simulate intangibles like human relationships and abstract institutions like governments. As your friendship develops over the years, you form mental representations of your closest friends that serve as guidelines for interacting with them going forward. Our models aid in foretelling what’s to come. According to your prediction, soup cannot be served with a fork. According to your prediction, your friend will be overjoyed to meet you next week.

Customizing Artificial Intelligence Predictions for Your Life

Using the mental models you keep in your head, you can make educated guesses about everyday occurrences. Your preparation for the professional licensing exam has been extensive and diligent. You should feel prepared for the licensure exam because you have already taken practice tests. Align your study routine with the practice test to increase your chances of passing the licensure exam.

How well will you do when you finally start working for your dream job? It will require a lot of time and energy. Is it in your nature to be accessible to your supervisor at all times? Is this challenging position something you’d enjoy?

If you want to be able to foretell events that happen in places where you don’t normally go about your business, you’ll have to keep a lot more personal data in your head. Even while human brains are the most complex and sophisticated of all living things, there are limitations, such as the fact that you can’t help but forget that you were a member of the high school track team until the schedule became too demanding. That is, you have demonstrated in the past that you prioritize leisure time over competitiveness.

How would you perform if your job doesn’t allow you any downtime?

Prediction AI

Everything you’ve been through up to this point will serve you well in the future. But suppose a supernatural being could remember every detail of your life’s events. Imagine a world where information about your past might be used to foretell your future self.

Whether you think of someone knowing your every move and being able to foretell your future as thrilling or terrifying, you can be certain that it is already a reality. Industry heavyweights will be incentivized to release personalized Prediction AI models faster due to your interest in the future.

A Model for AI Population Prediction Developed at Copenhagen

Danish academics created a fascinating experimental prediction model using a massive collection of personal information.

The Copenhagen group utilized an innovative line of reasoning to investigate how and why human lives change and are predictable in light of specific event sequences (“your life is like a sentence”). This line of reasoning uses A sentence as a metaphor for life. For instance, your likelihood of knowing the ending of a statement increases as its word count increases.

To illustrate the point, the phrase can be concluded in various ways using “I am…”, but “I am going to…” limits the range of viable conclusions. If an entity is aware of your habits—for example, you know that you usually go to a certain place on Fridays to unwind after a long workweek—then this entity could foretell your future, saying things like, “I am going to…Jake’s Bar after work to see friends.” More knowledge makes you more predictable thus your life is like a sentence.

PredAI’s prediction abilities are directly proportional to the information it has about you. Based on this assumption, the Copenhagen team obtained a one-of-a-kind and extensive dataset from the Danish national registration. The collection contained detailed recordings of everyday occurrences for about 6 million Danes during 10 years.

Researchers in Denmark used this national registry to compile data on the daily resolutions of Danes’ health, education, occupation, income, and working hours. Researchers proved that human lives may be described as linguistically equivalent sequences of events by incorporating this dataset into their large language model. These sequences can predict everything from early death to subtle behavioral traits.

Let’s Take a Brief Break Right Now.

Is this research starting to terrify you? Think about the book’s subtitle, “What Happens in a World That Anticipates Your Every Move,” written by Patrick Tucker. Every step you take as a Dane has been documented in the national registry. The data set enabled the Copenhagen team to develop a customized, population-based AI model for predictionConsider ethics and privacy.

But Before We Evaluate this Approach, let’s Look at How it Works.

Prediction AI

Using the Copenhagen Model and Its Potential

Using the nerdy moniker “life2vec,” the researchers showcased three “prediction tasks” that their AI model executed. This is their shortened way of saying “from life to vector,” which is another way of saying “from life to snapshot.”

  1. Mortality Prediction: The model can forecast the probability of early death within a certain time frame by examining the order of life events. To achieve this, it learns patterns that link specific event sequences to an increased likelihood of dying prematurely. A succession of multiple bad health-related events, for instance, may indicate a higher risk.
  2. Subtle Characteristics The model can also predict more complex parts of people’s lives, such as personality qualities. To achieve this, it learns to associate certain patterns in how people report their personalities with the sequences of events in their lives. More outgoing people may, for example, engage in social activities on a regular basis.
  3. Person-Summaries: Life2vec extracts a “person-summary”—a concise and all-encompassing snapshot (vector) that encapsulates the essence of an individual’s life’s journey—from a vast array of data, including medical records, educational achievements, employment history, and more.

This person-summary feature has to be examined more thoroughly.

Picture this: you’ve maintained an exhaustive journal of your life, recording every important event, from doctor’s appointments and job changes to life-changing moments and important financial decisions. Imagine for a second that you’re a subscriber to the life2vec program, which scans your journal entries and compiles all the information it has about you in a nutshell. Think of this picture as a unique code that sums up your narrative. The program will transform your own summary space into a “vector.”

This vector (snapshot) contains all the information that life2vec uses to make predictions about you, such as your future health or employment type. It considers the most basic information, such as your age, level of self-care, and income. It can also pick up on subtler aspects, like the nature of your work and how it could influence your future, that could otherwise go unnoticed.

You can tailor the precise data about yourself (your snapshot) to answer various inquiries about the future of a certain sector of your life based on your desires for future knowledge.

For instance, life2vec can show you how your current work situation might affect your future health. These insights can help you understand the “why” behind these AI forecasts for your future, and they can also get you thinking about things in new ways and asking questions you hadn’t considered before.

For future scenarios based on where you live, education level, age bracket, political affiliations, or any other demographic categories you can think of, life2vec’s three prediction tasks (person summary, mortality, and personality nuance) can do the heavy lifting.

The Dangers of AI Predictions

Having an AI personal assistant who can predict your behavior and advise you on how to proceed comes at a cost, though—an AI entity that is privy to your personal information. It will be more helpful to you if you tell me more about yourself.

Would you rather sacrifice some privacy?

Now that you know how powerful Prediction AI is, you can develop a list of concerns about your digital past. My list is this:

Proprietorship of the Prediction Model: Few nations possess a thorough and regulated system of citizen registries, except those in the Nordic region. With population-based prediction AI taking the lead, one must wonder who will own the data about your personal experiences. Is it safe to entrust this data to a private company run by a billionaire? Should the government have access to this data?

Consent, Data Protection, and the Possible Abuse of Sensitive Information are at the heart of the privacy and ethical concerns of using comprehensive personal data for population or individual forecasting.

Concerning bias and fairness issues, generative AI has occasionally been observed to “hallucinate,” producing inaccurate data. Inherent biases in your historical dataset may impact prediction AI projections, which could result in misleading or incorrect future scenarios. Poor planning or disastrous results due to poor guidance can result.

Relying Too Much on Prediction Models: Not everyone needs constant reassurance regarding the future. When making key health decisions, it is important to understand the complicated and multifaceted nature of human health and the limitations of PredAI, as an anxious person’s demand for certainty could cause them to rely too much on such models.

Prediction: AI Will Remain After It Arrives

Prediction AI is already making waves in numerous industries and will only grow in popularity. Healthcare systems incorporating Prediction AI and Generative AI into their early detection and diagnosis processes, personalized treatment plan creation, and predictive analytics of disease progression can achieve improved patient safety, efficiencies, and cost reductions.

The Time Has Come for Me to Make a Forecast

Neither humans nor computers could have foreseen the meteoric rise of generative AI. GenAI has already spread to nearly every facet of people’s lives and businesses. Imagine my surprise when, just 18 months ago, I used an AI bot to organize my trip to Europe!

Is Prediction AI destined for the same fate? Much like GenAI, PredAI is data-driven. However, to build patterns that can lead to predictions, PredAI needs trended and historical data. Regarding family trees, only a few countries have the kind of comprehensive databases that were vital to the development of the Copenhagen model.

The amount and variety of person-centered data necessary for the PredAI sector to thrive might be out of reach unless we consent to letting profit-driven major tech companies collect information about our lives.

The likelihood of PredAI’s sneaky intrusion into our lives is higher. For instance, when necessary, specialty practitioners in the system can access patients’ medical records kept by healthcare plans. By aiding doctors in forecasting the course of your recent diagnosis, a PredAI model is highly beneficial.

How much we feed Precision AI may ultimately determine its growth. A customized PredAI, whether a beast or an angel, will flourish when fed your life story.

What’s the most effective way to get ready for what lies ahead for PredAI? When first-timers in rodeo are about to endure the excruciating ordeal of mounting an enraged bull, seasoned cowboys would advise, “Know the bull and be ready for the kick!”

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