Project Strawberry Credit: king newswire
Introduction
AI models have made remarkable progress in the last three years. ChatGPT generates text at speed and increasingly so with incredible creativity. Aiva composes music, Sora generates videos and Midjourney generates art. Yet, when it comes to advanced mathematical reasoning – the kind of reasoning required to apply logic beyond surface-level patterns and even in unfamiliar contexts – these models often falter. While they may excel at solving routine problems, they struggle with tasks requiring deep understanding and they often break down when logic has to be applied in unfamiliar or unstructured ways.
Definition of Reasoning
Reasoning is the capacity to consciously apply logic by drawing conclusions from new or existing information, with the aim of seeking truth. It is closely associated with human assets such as philosophy, science, language, mathematics and art. In the past reasoning was considered to be a distinguishing ability possessed only by humans. While reason implies a sense of rationality, reasoning is associated with the acts of thinking and cognition and involves the use of one’s intellect. The field of logic defines the ways in which humans use formal reasoning to produce logically valid arguments. Reasoning may be subdivided into concepts of logical reasoning, deductive reasoning and inductive reasoning. In some social and political settings logical and intuitive modes of reasoning may clash, while in other contexts intuition and formal reason are seen as complementary rather than adversarial. For example, in the field of mathematics, intuition is often necessary for the creative processes involved in arriving at a formal proof which is likely the most difficult task of formal reasoning. Moreover, reasoning is one of the ways whereby the process of thinking moves one idea to a related idea. For example, reasoning is the means by which a rational individual understands sensory information from his environment. This conceptualizes abstract differences such as cause and effect, truth and falsehood or ideas regarding notions of good or evil. Reasoning, as part of executive decision making, is closely identified with the ability to self-consciously change in respect to one’s goals, beliefs, attitudes and traditions, thereby fostering the capacity for freedom and self-determination. Using reason or reasoning, can also be described as the process to find the best solution to a given problem. For example, when evaluating a moral decision, ‘morality’ is, at the very least, the effort to guide one’s conduct by reason while giving equal and impartial weight to the interests of all those affected by what one decides. Psychologists and cognitive scientists attempt to study and explain how people reason, for example which cognitive and neural processes are engaged and how cultural factors affect the inferences that people make. As a result, several theories have emerged as to how reasoning affects human behaviour. However, it is too early to forecast which theory will prevail.
Intelligence and Reasoning
Reasoning, problem solving and decision-making represent different as well as overlapping aspects of human intelligence. Researchers following the cognitive psychological approach to reasoning, study the responses of a small number of participants to logical tasks such as syllogisms or formal deductions analysing a given problem. The current theories dominating psychological concepts in respect to reasoning and their relationship to intelligence are defined by mental rules and mental models. These theories were first applied to the study of deductive reasoning tasks and thereafter applied to a broader range of tasks. Human reasoning occurs at different levels of awareness. Most cognitive scientists distinguish between tacit and intentional or explicit reasoning tasks. One of the important controversies concerning reasoning and intelligence is the extent to which individuals differ in their reasoning abilities and the capacity of their neural working memory. Traditionally, IQ-tests such as the Cognitive Abilities Test have been used to provide a measure of cognitive development and human intelligence. However, more research is required to understand the relationship between intelligence and reasoning, especially in the context of machine vs. human reasoning.
The Evolution of AI and Reasoning
In the early days of AI, machines followed strict, pre-programmed rules, performing tasks without much flexibility. These systems could only execute what they were told, lacking any true understanding or problem-solving ability. But as technology advanced, AI shifted toward machine learning and neural networks. Systems began to learn from data and improved their performance over time. This allowed AI to recognize patterns and make predictions, but still without real reasoning.
Now, we are witnessing the rise of AI with actual ‘reasoning’ abilities. Intelligent machines can analyse data and make decisions, adapt to new information, and solve complex problems on their own, much like a human would. However, as AI has made great steps in reasoning, it is still not close to replicating human thinking. Unlike individuals, who can think critically, creatively and emotionally, AI’s reasoning is based only on patterns and data it has been trained on. Moreover, AI systems often reflect biases present in the data they are trained on, which can lead to unfair or discriminatory outcomes. If an AI is trained on biased information from the past, the AI’s decisions can be wrong. AI can only reason based on what it has been taught, so it struggles with situations it has not been trained for. This makes AI less flexible and adaptable compared to human thinking.
Reasoning in Real-World Applications
AI is reshaping industries, making a real impact in healthcare, finance, law, robotics, and education. The following provides a brief overview: In healthcare, AI is helping doctors detect diseases earlier and more accurately. The NHS is running the world’s largest trial for AI breast cancer detection, analysing 700,000 mammograms. Northwell Health’s AI tool, iNav, spots pancreatic cancer early, speeding up treatment, Meanwhile, ‘C the Signs’ identifies high-risk cancer patients with impressive accuracy, showing how AI can save lives by spotting issues early. In finance, AI is changing how we assess risks. It analyses vast amounts of data to predict trends and identify potential problems such as the 2023 Silicon Valley Bank collapse. AI tools from Bloomberg and Tiger Brokers help investors make faster, smarter decisions, reducing losses and sharpening financial strategies. In law, AI makes legal research faster and more accurate, predicting case outcomes by quickly sifting through vast amounts of case law. In robotics, AI-driven machines are getting better at making real-time decisions in ever-changing environments. In education, AI tailors lessons to individual students, improving learning by adapting to their needs.
Will AI Ever Think Like Humans
As AI gets smarter, new technologies are being created to help it think more like humans. Scientists are working on ideas like neuro-inspired AI and cognitive architectures, which tries to copy how our brains process information. The goal is to make AI more flexible, so it can understand things better, adapt to changes, and think quickly, just like we do. If these ideas work, AI might one day be able to think as creatively and deeply as humans. But there are also some issues to consider. Can AI ever really think like humans? Some researchers believe it is impossible because AI does not have emotions, consciousness, or free will, capabilities that make human thinking so unique. Others wonder if we even want AI to think like us, considering the risks and ethical challenges that might come with it. Regardless, humans will still play a key role in guiding AI’s reasoning ability. AI should be a tool that enhances what we can do, not something that replaces our judgment, values or decision-making. After all, it is our unique human perspective that keeps things in perspective.
Conclusion
AI is learning to solve problems and adapt in ways once considered only humans could do. Looking ahead, AI’s ability to reason could change technology and its application for solving problems forever. But it also raises questions regarding fairness, control, and responsibility. While the future is exciting, there are challenges we still need to solve, like making sure AI supports our decisions without replacing them. We are just starting a new chapter in technology, and it is up to all of us to decide how AI grows and fits into our world. AI’s reasoning capabilities or lack thereof appears to disturb many of us. Admitting that AI can ‘reason’, is perceived as a provocation to human’s identity and values, as reasoning would not be exclusive to humans.