The Biggest Challenges in Implementing AI
Learn about the potential challenges that AI developers need to address to make sure that AI is accepted as a friend and not as a foe.
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As we all know, there are pros and cons associated with every technology — and AI (artificial intelligence) is no exception to this rule. However, it becomes very important for us as technology consumers and producers to identify those challenges and minimize the associated risks and at the same time make sure that we take full advantage of this technology.
In this article, I will break down the potential challenges that AI developers need to address to make sure that AI is accepted as a friend and not as a foe, given the kind of media attention it is getting — especially around the fact that it is going to take away our jobs.
The widespread use of AI raised a number of issues that have yet to be addressed. As we know, AI bots are becoming better at mimicking human conversations. For example, in 2015, a bot named Eugene Goostman won the Turing Challenge for the first time. In this challenge, human raters used text input to converse with an unknown entity, then guessed whether they had been chatting with a human or a machine. Eugene Goostman fooled more than half of the human raters into thinking that they'd been talking to a human being.
Now, think about this capability getting into the wrong hands. What havoc could it wreck? How could it prove to be detrimental to society? The most popular are dating bots, where a computer program (chatbot) that uses artificial intelligence strikes up conversations with dating site users, enabling the scammer to "talk" with multiple potential victims at once. These discussions are primarily aimed to trick and get users to send them money or download malware onto their PC.
This may also be targeting victims for identity theft or other criminal activities. This is one of the many ethical challenges that AI might pose to society.
Legal challenges related to AI's application in the financial industry could be related to the consequences of erroneous algorithms and data governance. Erroneous algorithms, due to the lack of appropriate data, can leave a big dent in the profits of an organization by making incorrect and perhaps detrimental predictions. Poor data governance can result in data breaches where customers' PII (personal identifiable information) that acts as a feedstock to an algorithm may get into the hands of hackers and can cause legal challenges for the organization.
Most researchers believe and agree that a superintelligence AI is unlikely to showcase human emotions like love or hate and that therefore, it cannot become intentionally benevolent or malevolent. However, the most likely scenario where it can pose a threat to the society is via autonomous weapons. These are weapons that AI systems are programmed to use to kill. If in the hands of the wrong person, these weapons could easily cause mass casualties. This could even lead to an AI war that would also result in mass causalities.
It is worth mentioning that Stephen Hawking, Elon Musk, Bill Gates, and many other big names in science and technology have recently expressed concerns about the risks posed by AI. Because AI has the potential and power to be more intelligent than any human, we have no sure way of predicting how it will behave.
Not everything you hear about AI is true. Let's look at few myths related to AI and clear up some of the most common misconceptions about it.
After looking at a few challenges and threats related to AI, it is my duty to talk about its benefits as well. I couldn't find anything better than this visual produced by narrative science around how AI is helping business owners make data-driven decisions:
Source: Narrative Science
Dave McCandless had stated that data is not the new oil — it’s the new soil, as it acts as a fertile land to nurture and grow the digital economy. AI can help organizations mine for the golden nuggets found within their databases by processing billions of data points in a fraction of minutes. The best part is that AI is dynamic in nature as it is always learning and adapting to the new trends.
Industries such as manufacturing, RPA technology has made simple yet time-consuming tasks automated and helped the industry to free its valuable resources to do more specialized work. It has helped leading organizations become more productive so that more time and money can be invested in engaging with the workforce. This, in turn, creates a solid and caring organizational culture and keep the employee turnover low.
In the end, I would just like to say that the key to success with AI is to not be seduced by its capabilities. No technology offers a silver bullet. Rather, organizations should focus on how they can responsibly reduce the ill effects of this technology by minimizing the challenges and leveraging the benefits and by creating a clear technology adoption roadmap that understands its core capabilities.
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