Five major problems of artificial intelligence in 2018

This article explores the five key challenges that artificial intelligence faced in 2018, including understanding human language, improving robotic capabilities, enhancing security against hacking, advancing AI in gaming, and enabling ethical decision-making. Addressing these issues is crucial for ensuring that AI continues to serve humanity effectively and responsibly.

In 2017, AI made significant strides, largely due to advancements in deep learning. One notable example was Libratus, an AI poker player that defeated top human players, earning the nickname "Alpha Dog" in the poker community. Beyond entertainment, AI has begun transforming industries such as healthcare, agriculture, and autonomous driving, making everyday life more efficient and safer.

Despite the rapid progress, some experts question whether the current pace of AI development is sustainable or if there's a bubble in the field. Media speculation often exaggerates AI's capabilities, but there are also thoughtful voices warning about the real challenges ahead. Elon Musk, for instance, expressed concerns that AI still lacks the depth to truly understand complex human tasks, pointing out that the toughest problems remain unsolved.

Understanding Human Language

While AI has become remarkably good at processing text and language, it still struggles to grasp the deeper meaning behind human communication. For example, Facebook can describe images for visually impaired users, and Google Mail can draft simple responses based on email content. However, true comprehension—understanding context, intent, and nuance—remains elusive. Melanie Mitchell, a professor at Portland State University, highlights that while humans can apply knowledge creatively in new situations, AI is still limited by its inability to do so. This challenge is referred to as a “meaning barrier” by some researchers, and efforts are underway to bridge this gap by teaching machines common sense and world knowledge.

Make the Robot More Like a Person

Robotic hardware has advanced significantly, with affordable drones and bipedal robots becoming more common. However, without intelligent software, these machines lack the cognitive abilities needed to perform complex tasks. Programming each task individually is time-consuming, so researchers are exploring simulation-based training to speed up learning. While virtual testing helps, there remains a “reality gap” when transferring skills to physical robots. Still, progress is being made, as seen in Google’s simulated robotic systems that successfully manipulate real-world objects.

Prevent Hackers from Attacking AI

As AI becomes more integrated into daily life, security vulnerabilities grow. Researchers have shown that malicious actors can embed hidden triggers in AI models, causing them to behave unpredictably. For example, a street sign recognition system could be tricked into misidentifying a parking sign as a speed limit sign. These threats have led to increased focus on AI security, with conferences dedicating entire sessions to discussing how to protect machine learning systems. Experts warn that AI could be used for deception, such as generating fake videos or audio, raising serious ethical concerns.

Where Is the Real Future of AI Games?

AI’s success in games like Go and Chess has been impressive, with AlphaGo Zero demonstrating remarkable skill without human input. However, these games have clear rules and structured environments, unlike the unpredictable nature of real-world problems. To push AI further, researchers are now tackling complex games like StarCraft, which require strategic thinking, memory, and adaptability. Despite initial challenges, progress is being made, and future breakthroughs in game AI could lead to broader applications in real-life tasks such as business operations and military strategy.

Let AI Distinguish Between Right and Wrong

Even if AI doesn’t advance in all areas, its widespread use already has profound societal impacts. Concerns about bias, fairness, and safety are growing, especially as AI systems make decisions in critical fields like finance and healthcare. At major conferences, discussions on ethical AI have become central, with researchers working to develop tools that ensure transparency and fairness. Institutions and companies are beginning to prioritize ethics, calling for regulations to prevent the misuse of opaque algorithms in sensitive areas like criminal justice and social welfare.

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