As AI-driven prediction models like ChatGPT’s I-Ching plugin and Denmark’s life2vec enhance predictability across various aspects of life, the ethical challenges they pose, including data security and bias, underscore the need for a thoughtful balance between technological advancement and ethical considerations. 🔮🤖 #AI #Ethics #PredictiveModels
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Happy New Year of 2024!
Welcome to 2024, and Happy New Year! At last year’s New Year’s Eve dinner, we reminisced about the past and pondered the future. Some friends, well-versed in the I Ching, shared hexagrams that hinted at the year ahead—a tradition in China for predicting fortune and development. It got me thinking about the ever-popular ChatGPT, which boasts numerous plugins, including fortune-telling conversations. Isn’t it fascinating how artificial intelligence can wear many hats, from your work assistant to predicting your future? The I Ching, with its intricate calculations, shares a common purpose with AI in its quest to uncover hidden truths.
How to Utilize the ChatGPT I-Ching Plug-In
Using the ChatGPT I-Ching plug-in is a breeze. Simply search for and install the I-Ching (Book of Changes) plug-in within ChatGPT. Then, pose a question that’s on your mind—it can be specific or a broader inquiry. Allow the plug-in to interpret the image for you. For instance, you might ask, “What are your predictions and evaluations of my new job development?” Each interpretation is distinctive, and it’s up to you to gauge its usefulness.
Predicting Human Life with AI at the Technical University of Denmark
hatGPT is not alone in this endeavor, as a novel artificial intelligence system, developed at the Technical University of Denmark, is also making strides in this field. Led by Sune Lehmann, the project aims to predict life events and human behavior—an approach increasingly adopted by tech companies internally to profile and influence individuals based on their social network activities.
In a recent scientific article titled “Using Life Event Sequences to Predict Human Lives,” published in Nature Computational Science, researchers harnessed health data and labor market insights from 6 million Danes to create a model called “life2vec.” This model, trained to recognize patterns in data, surpassed other advanced neural networks and achieved remarkable accuracy in predicting outcomes such as personality traits and even the timing of individuals’ deaths.
The key to this breakthrough lies in organizing the vast database into chronological “life sequences,” enabling the AI to predict subsequent events much like an AI chatbot predicts the next word in a sentence. Between 2008 and 2016, the model was trained on the life sequences of individuals aged 25 to 70 and successfully predicted the next four years, outperforming existing state-of-the-art models by an impressive 11% when assessing the likelihood of someone passing away during that period. This groundbreaking model holds promise for a future where it can provide various insights into human life and address individual health inquiries.
Navigating Data Security and Ethical Concerns
The advancement of artificial intelligence invariably raises ethical considerations, and the life2vec model developed by Danish researchers is no exception. Ethical dilemmas surrounding this model include safeguarding sensitive data, ensuring privacy, and addressing potential biases inherent in the data. Prior to deploying this model, a thorough understanding of these challenges is imperative, particularly when assessing an individual’s risk of experiencing a disease or other preventable life events.
Whether it’s ChatGPT’s predictive model based on I Ching hexagrams or the life2vec model driven by extensive data from the Technical University of Denmark, an increasing number of predictions across various domains are reshaping our understanding of life, work, society, and health. The question arises: might humanity eventually find itself ensnared within AI models? While the future holds promise, it’s essential to tread carefully, balancing technological progress with ethical considerations.