The challenges of Consumerization of AI based technologies

Siddharth Behera
Mar 5, 2018 · 6 min read
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The conduct of knowledge management is changing fundamentally due to consumerization of Information Technology. The consumerization of Information Technology is transforming the way knowledge workers conduct work and share knowledge and information. But the question is, what consumerization actually is? Answer ,Consumerization is the reorientation of product and service designs to focus on the end user as an individual consumer, in contrast with an earlier era of only organization-oriented offerings .

Technologies whose first commercialization was at the inter-organization level thus have potential for later consumerization. The emergence of the individual consumer as the primary driver of product and service design is most commonly associated with the IT industry, as large business and government organizations dominated the early decades of computerusage and development.

Now the AI technology is presently very agile. It is hard to pinpoint the exact path that AI will take, but with companies such as Google, Facebook and Microsoft making huge strides, AI or artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision and AI.

In 2014, Google bought artificial intelligence startup DeepMind for a whopping $400 million (£263 million) to complete one of the largest AI acquisitions to date.Google has also made its machine learning system TensorFlow free to anyone who wants it, and in July 2017 it launched a new project to study and redesign the ways people interact with AI systems called People + AI Research initiative (PAIR)

The very idea to create an artificial intelligence is to make the lives of humans easier. Here is one such highlight able example. According to The Next Web, Facebook is helping blind people ‘see’ photos by using artificial intelligence to narrate them via its iOS app. By using neural networks, the Facebook app will generate a description for every photo e.g. ‘three women smiling with champagne’.

In addition, Facebook is reportedly using artificial intelligence to produce detailed maps illustrating population density and the access to internet across the globe. This should help Facebook bring internet to parts of the world that are without access. Facebook has analysed 20 countries and 21.6 million square kilometers amounting to 350 TB of data.

AI has also accentuated the capability to automate medical diagnostics by mining patient records and the scientific literature. This technology will allow doctors to focus primarily on dimensions of care while utilizing their experience to guide the process. Personalized medicine will soon become a reality owing to the data obtained from patient records, wearables, mobile apps, and personal genome sequencing. IBM’s Watson is already assisting oncologists to process patient data for them to make better decisions about treatment.

The complete transition to an AI-guided transport system will soon be a reality, as companies like Google, Uber, and General Motors are striving hard to establish themselves at the top of this market. From Google to Uber to General Motors all want a piece of the fast-growing market for driverless vehicles. The algorithms designed to enable machines to learn from human inputs will be crucial in ensuring that these systems operate smoothly and efficiently. So we can easily uphold the fact that AI can help humans by humans immensively . But us it that easy?? Let’s find out ..

Nurturing a desire to learn is very important for all humans . The same goes with the computers as well . Although we are not at the level to make them feel human sentiments but still the challenge remains on how we can make them competent enough to mimic most of the activities we can do .We need a wide arrays of algorithms , vast knowledge of mathematics especially probability and statistics and most importantly a very good set of data. A good variety of relevant DATA is extremely crucial for making the AI software work as we wish to. Essential for the successful operation of any business, these data make the core of the AI and decision-making triggers throughout a company. To maximize value, AI/analytics apps must be aligned with each of these data. “To train machine learning algorithms one needs massive and clean data sets, with minimum biases,”.

AI has enabled all of the corporate business world to understand the taste of their customers very well .Netflix’s ads are a live example. A sophisticated AI identifies many things like what genre of stories the customer likes and suggests more of that specification. But this is a big challenge. Traditional consumer apps are a bit unrelated like a consumer may use one app to find the closest gas station and another to find the closest Italian restaurant. Although both these apps serve the needs of the same consumer, they don’t necessarily need to be connected to each other. Business apps must be connected with each other in a logical manner, and they have to deliver the analytic insights in a form that the human talent can easily interpret and maximize the monetization potential. It’s interesting to envision a complex collection of AI-driven components collaborating to create fully automated, perfectly personalized customer experiences. But that system may have high frequency of failures as one or another component finds itself facing conditions it wasn’t trained to handle. If the systems are well designed and we’re lucky, the components will shut themselves down when that happens. If we’re not so lucky, they’ll keep running and return increasingly inappropriate results.

In the case of customer marketing, there are many aspects to consider and the AI has to see which aspect has to be given more priority that is the categories have to be properly contextualized as per the requirements, by requirements we mean here some very SPECIFIC requirements. Because the returns can vary so much depending on the brand and its needs, companies will realistically need to analyze AI technologies and determine which ones offer the most value to them.For example, one company might realize significant value applying AI to lead scoring while another might realize more value applying AI to social media sentiment analysis.

But even so, AI applications lack emotional intelligence, and most importantly, they are unable to demonstrate empathy, and this is a huge barrier to AI success in customer service applications such as chat-bots. After all, certain customer service inquiries creates a make or break situation for the customer relationship. While there is evidence that AI is capable of creating certain kinds of content that is virtually indistinguishable from human content in terms of clarity and accuracy, machine-produced content is substantially more boring and less pleasant to read according to one study.

So the end result comes out to be despite the emerging technologies, there are challenges and AI presents no shortage of them. That might explain why, according to a new MIT-Boston Consulting Group survey, 85% of executives believe AI will change business, but only 20% of companies are using it in some way, and just 5% make extensive use of it.

There’s another undesirable social phenomenon which hinders the growth of AI .There are many debates on this topic. Whether humans can unnecessarily be highly dependent on the machines if the use of artificial intelligence becomes rampant. They will lose their creative power and will become lazy. Also, if humans start thinking in a destructive way, they can create havoc with these machines. In the recent times and in near future, the need of having beneficial effects of artificial intelligence on the society has motivated research in many areas like security or control to nontechnical topics like economics and law. While laptop crash might be a little trouble, but this is a highly undesirable event if it is an airplane autopilot software malfunction or a lapse on your trading terminal or even your power grid monitoring. Lethal autonomous weapons are also a product of artificial intelligence and the near future challenge is to control the same.

However we must note that everything that has been created in this world and in our individual societies is the continuous result of intelligence.AI augments and empowers human intelligence.So long as we are successful in keeping technology beneficial, we will be able to help human civilization . As the old saying goes, ’the need is the mother of all innovations’, so it is with AI. Humans are getting increasingly better in defining their needs and quickly transforming them into reality. If we just avoid the social issues, AI will soon be tackling all it’s cons and shall be a vital aspect in business and then there will be an era for consumerization of AI all around the world.


Official publication of E-Cell | NIT Rourkela

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