5 major AI fails that highlight the technology's limitations
Here are the top 5 AI fails that broke the internet and made headlines!
Artificial Intelligence (AI) has undoubtedly revolutionised the way we live and work, with innovations like voice assistants, self-driving cars, and personalised recommendations becoming increasingly common. However, AI is not without its flaws.
In today's article, we'll explore five AI fails that highlight the limitations and challenges of this rapidly advancing technology.
Top 5 AI fails that broke the internet
1. Deepfake scams
Deepfake technology uses artificial intelligence to create very realistic fake videos, which has led to a lot of fabricated content and online abuse. This AI tech has been highly misused globally, from spreading misinformation to scams.
Generally, deepfakes of celebrities and influential personalities are morphed to lure users into fraud. Recently, Deepfake Elon Musk became the internet's biggest scammer as 82-year-old Steve Beauchamp got tricked into paying $690,000 through a series of transactions.
Another big incident happened when a senior employee was duped to pay $25 million to a fraudster posing as the CEO of the firm. These cases indicate the dangerous misuse of AI-powered deep fake technology. According to Deloitte's Center for Financial Services estimates, generative AI could enable fraud losses to reach $40 billion in the United States by 2027.
2. Self-driving cars
Self-driving cars heavily depend on AI to make decisions, but they've encountered difficulties in recognising unanticipated obstacles, resulting in accidents.
A tragic incident involving an Uber self-driving car in 2018 raised serious worries about the safety of AI-powered vehicles. Similarly, a Baidu-operated driverless car hit a pedestrian in Wuhan. And, so far, Tesla's Autopilot feature has been linked to 13 fatal accidents, sparking intense scrutiny of autonomous vehicle technology.
In the United States, automotive AI was the reason for 25 deaths, injuries and property damage. Since artificial intelligence cannot understand like humans, it lacks safety measures.
3. Chatbot blunders
Businesses are increasingly using chatbots to automate customer service interactions and streamline communication processes. However, these conversational AI systems can sometimes give inaccurate responses.
For example, in 2016, Microsoft's chatbot Tay posted offensive tweets within 24 hours of launch. Later on, the firm quickly took Tay offline to mitigate the damage. Moreover, the internet was recently flooded with memes of AI chatbots failing to spell the simple word "Strawberry".
While AI-powered chatbots have the potential to enhance customer experiences, they must be carefully designed and monitored to avoid costly mistakes.
4. Healthcare misdiagnosis
AI applications in healthcare have shown great promise in diagnosing diseases, predicting patient outcomes, and personalised treatment plans. However, there have been instances of AI systems making mistakes due to limited or biased data inputs.
In one case, an FDA-approved AI breast cancer screening tool was found to be less accurate for black women. This issue highlights the need for diverse and representative datasets for AI training. Another instance was when IBM's Watson for Oncology faced criticism for providing inaccurate treatment suggestions, leading to concerns about its reliability in real-world medical settings.
As we rely more on AI in healthcare, it is crucial to address issues of algorithmic bias and ensure that these systems are rigorously evaluated and validated before being deployed in clinical settings.
5. Weird AI features
Everyone had eyes on Microsoft's developer conference this year amidst the AI trend. While the software giant did announce many things, it particularly gained attention on "Recall". For those unaware, this tool takes screenshots of everything you do at regular time intervals so that users can retrieve what they were doing.
Even Elon Musk stated the "Recall" feature reminded him of an episode of Black Mirror, a popular series portraying the dark side of technology. Similarly, this feature creeped out many internet users which led to Microsoft delaying its release. On the other hand, when Google AI Overviews was being experimented with in the US, it gave false answers and wrong information which again received heavy criticism.
AI is not the answer to everything
While AI has the potential to transform industries and improve our daily lives, it is crucial to recognise and address the limitations of this technology. By understanding the potential pitfalls of AI systems and working towards more ethical AI development practices, we can harness the power of AI responsibly.
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