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Niches where AI faces limitations

byEditorial Team
May 6, 2024
in Artificial Intelligence

Artificial intelligence (AI) has definitely changed different industries by improving skills and reshaping processes. AI has made tremendous progress; still, there are some areas where AI’s ability is insufficient. Insight into these limitations is crucial for understanding the current state of this technology and its effective implementation in different areas. In this article, we will dive into some of these areas where AI encounters roadblocks to understand why this happens.

Creative arts

AI is outstanding at creating art, music, and literature, but the extent to which it can imitate human creativity is limited. Content production using AI frequently lacks the depth, emotion, and originality that are characteristic of human production. The intricacies of artistic expression and the ability to elicit complicated emotions are areas where AI cannot match human creativity.

Investing

AI has completely revolutionised the financial sector, optimising operations and improving decision-making. Nevertheless, AI’s advantages are counterbalanced by some limitations when it comes to investing. AI models can process large datasets and spot patterns that lay the foundation for investment strategies, but they may miss something unpredictable or unexpected that could seriously impact financial markets. Relying on the knowledge of financial advisors like CEO Nicolai Chamizo has proven to be much more efficient regarding long-term investing.

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Niches where AI faces limitations
Nicolai Chamizo

Ethical decision-making

AI decision-making skills are very constrained when it comes to resolving complicated ethical issues. While AI may be able to optimise processes for the given objectives, it lacks the moral reasoning and empathy needed for a nuanced ethical judgment. The problems of fairness, justice, and human rights are the main problems for AI systems, especially in situations where it is impossible to distinguish between right and wrong.

 

Common-sense reasoning

Artificial intelligence has made remarkable gains in natural language processing and understanding but has not conquered the challenges of common-sense reasoning. AI also lags in understanding context, interpreting meaning, and drawing inferences bound by logic. Hence, AI’s inability to enjoy such dialogue, understand a subtle joke, or solve everyday problems that require common-sense knowledge could hinder its capacity to perform in these areas.

Physical dexterity and perception

Although AI-controlled robots have shown great and incredible capability in precise and controlled environments, they are, however, weak in operations that demand fine motor skills and more human-like perception. The robotic systems currently driven by artificial intelligence are still challenged with tasks that barely require a high level of complexity, such as folding clothes, manipulating delicate objects, or navigating through crowds in a smart manner.

Complex strategy games

The media has been buzzing over AI’s successes, such as its victories against human champions in chess and poker. While such games with incomplete information, concealed interests, and complicated social dilemmas may show obstacles, human nature and morality cannot be neglected. Strategic games like diplomacy that are characterised by negotiations and cooperation can present challenges to current AI systems because they require higher levels of strategic thinking and interaction with others than what these current systems can produce.

Medical diagnosis and treatment

AI has already demonstrated its ability to aid medical practitioners in diagnosis and by providing recommendations on treatment management. While AI can potentially transform the healthcare domain, the complexity of human physiology, the spectrum of disease manifestations, and the ethical dimensions of healthcare choices pose formidable obstacles on the AI path.

Recognising these limitations is the first step in forming realistic expectations necessary for safe AI deployment. In order to resolve these problems, there should be interdisciplinary collaboration, ongoing research, and the ability to view the matter in a deeper and more subtle way. With AI being the focus of constant research and development, it is equally important to recognise its constraints in order to ensure ethical utilisation of the technology for the benefit of society and the progress of mankind.


Featured image credit: Steve Johnson

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