The Dark and Bright Sides of Artificial Intelligence (AI) Development

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Artificial intelligence (AI) is increasingly becoming a part of our day-to-day lives. Technological innovations are adopted even in traditional industries such as the oil and gas sector. 

Computers, virtual assistants, as well as cars and navigation are now being driven by AI and related technologies. AI capabilities are developing rapidly, and bots are now gradually replacing humans. For the continued evolution of AI, it is critical that developers continue their efforts in terms of research and development. 

AI devices and bots are now able to work on decision trees and think in a manner similar to humans. Also, these AI devices can work on a range of applications compared to humans who have limited capabilities. As is the case with the development of any new technology, AI development has its bright as well as dark sides.

First, let’s look at the bright side of AI development. Any developer working on AI technology sees this as a great opportunity since AI has multiple uses in the daily lives of humans. 

One new AI project could lead to a mainstream product which could add more comfort to human life. In case the product is well received in the market, the earning potential can be huge. AI earnings can materialize in the form of royalties, patent sales, as well as the sale of actual products and services. Further, once an AI project has been completed, the scalability factor is usually high. This is because replicating AI products can be relatively straightforward. 

Additionally, AI projects can be enjoyable to work on, simply because the end results can be unpredictable and often challenging. For example, the initial testing phase of AI-driven cars was a really exciting project which was picked up by various developers including big brands such as Google and Uber. 

The potential of such ground-breaking AI projects can be really high. AI-driven cars, for example, would totally eliminate the need for having human drivers. Such AI development projects have the ability to revolutionize and completely change certain industries. 

Further, working on AI-driven automation projects can be very useful in terms of learning. Development teams which are working on such projects have the potential to develop their own skills rapidly by understanding AI and related concepts such as machine learning. 

AI development also has another bright side. Development teams working on such revolutionary projects can gain widespread recognition for their efforts. For instance, the developers of AI-driven navigation systems were not only recognized around the world, but they also received various awards as well as other accolades. AI projects are unique in the sense that they can present the development team with a chance to have their moment of glory, but only after putting in loads of hard work and research. If the final AI product manages to save some time and money for humans, it is considered to be a great success, and the developers can have their moment in the sun!

While there are a lot of positives for the development of AI, there are also certain drawbacks. 

Initially, establishing the right area for research and development can be a great challenge. Since AI can be used for such a wide variety of applications, it can be hard to choose a particular area to explore. 

Once the area of AI research and development has been established, there can be various other dark sides as well. For instance, it can be hard to predict machine learning behaviour, which is a key element of a lot of AI-driven projects. 

Any hurdle, be it small or big, can prove to be the deal breaker in AI research. Since AI devices and bots do not react like humans, unpredictability is always a factor. For example, despite all the time and funds invested in AI-driven cars, they are still not thought to be fully reliable. Often, such cases can lead to a total loss in terms of the funds and time invested in the project. 

Further, it is a common practice to see budgets being exceeded in AI projects. This is because the outcomes of the research conducted in such projects are not certain and may require further modeling. 

Additionally, it is critical for developers to understand where to stop. AI can be really useful in general, but AI-based automation can also fail drastically if the environment is not conducive. For instance, there have been cases where AI-driven navigation systems have totally collapsed due to external causes such as natural calamities. 

It is critical for a developer to understand the limitations associated with AI because it can have a major impact on the daily lives of the end-users. 

Further, there could be cases when AI driven machines and bots fail to understand user commands, and this could pose a threat to the wellbeing of end users. 

Finally, some AI projects can be a major source of frustration for developers if the desired outcome is not achieved. A good example of this is the use of AI in Air Traffic Control. Although this technology was conceived and developed a few years ago, it has yet to be fully commercialized, leading to doubts over its long-term viability as well as scalability. Making air traffic fully automated can pose a number of security risks which can be damaging for such fields of AI research.

To sum up, AI has simplified human life a great deal, and it continues to do so. However, the development of new AI technologies has its set of drawbacks as well. Hence it is critical for any team of developers to strike the right balance so as to minimize the dark effects of AI and utilize the bright aspects to their fullest. In this way, end-users will benefit a great deal from AI, and developers will also reap their due rewards. 

AI technology, if developed and implemented correctly, can lead to a win-win situation for the individuals developing it as well as the ones using it.


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Anna Clarke is the owner of online writing company 15 Writers. She is a successful entrepreneur with over 20 years’ experience in both freelancing and academic writing industries, specialising in Business, Economics, Finance, Marketing and Management.

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