Artificial intelligence is truly amazing… but it’s not amazing at everything.

That’s a fair assessment, right? AI has captured the attention of the tech industry and mainstream culture over the last few years. It undeniably has fantastic potential, but also clear limitations and dangers associated with it.

While AI developers strive for true human-level reasoning, it remains just beyond our reach - for now. In this article, we’ll look at just how close we are to achieving this goal, and why we should tread carefully from this point on.

AI Disrupts Industries

AI has revolutionised the field of computer programming, altering how software is developed and implemented.

Historically, AI development involved crafting algorithms relying heavily on human ingenuity, like the Haar Cascade algorithm (that can detect objects in images, irrespective of their scale in image and location). Today, however, AI leverages self-learning systems, particularly evident in the realm of deep learning and neural networks.

Deep learning models, such as Convolutional Neural Networks (CNNs), excel at identifying patterns within data. AI's ability to process and learn from large datasets has opened new avenues in fields like computer vision, where it autonomously discerns complex patterns from images, but also in its ability to extrapolate conclusions from large datasets at a speed hard for humans to match.

Nonetheless, these models, despite their sophistication, do not truly understand the input but instead simply recognise patterns that correlate to expected outcomes.

Pattern Recognition

While pattern recognition is one of AI’s greatest strengths, its performance often plateaus when it comes to tasks demanding actual reasoning.

For example, language models might correctly answer questions or solve puzzles that follow familiar patterns, but they can answer with incorrect responses or run into errors when required to reason through novel situations or nuanced challenges, suggesting, perhaps, an improbable move in a chess game due to lacking contextual understanding.

The Human Element in AI Development

The limitations of AI underscore the irreplaceable role of human oversight. Even with AI as advanced as it is right now, there is a clear need for developers to maintain an active role in interpreting and correcting AI-generated outcomes. AI systems might generate plausible solutions, but without thorough human review, these solutions could propagate errors or miss critical ethical and logical nuances.

Ensuring Ethical Innovation

Looking ahead, the development and deployment of AI should focus on transparency and ethical considerations. As AI models approach ever closer human-reasoning abilities, developers must prioritise systems that delineate how decisions are made, ensuring ethical standards are met. This transparency will be key in navigating potential ethical issues and innovating safely within the field.

While company owners will of course make decisions around their impact on the bottom line, we would hope that many would see the benefits of having collaboration between AI and humans, rather than simply striving to replace them with AI technology entirely.

Equally, as developers, understanding the strengths and limitations of AI will empower us to better utilise these tools, closing the loop between what AI can suggest and what human logic can conclude.

Conclusion

As we said at the beginning of this article, artificial intelligence is truly amazing… but the truth is it probably never will be amazing at everything. Trained on average data, AI will always produce average results, and while humans are far from perfect, the two working together can produce incredible results, if we just understand both sides a little better.

For more on how AI challenges us to think differently, we recommend you check out Jonas Andrulis’ session from the WeAreDevelopers World Congress 2024, available on our watch page now.

Jonas Andrulis' The Shadows of Reasoning - New Design Paradigms for a Gen AI World
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