With the collection of data, processing and analysis to generate vital insights is becoming the backbone of decision-making for businesses. They are integrating new frameworks for effective data handling. The volume of data being generated by humans and sensors cannot be handled just by humans at scale. This data that is being seeded from modern artificial intelligence (AI) is assisting data scientists in integrating it into the process of mechanical manipulation and, eventually, AI. However, this discussion is also giving rise to a new stream of argument on the disadvantages of Artificial Intelligence (AI).
Two significant subsets of artificial intelligence (AI) - machine learning (ML) and deep learning are becoming valuable and effective tools for interpreting and analyzing data. While artificial intelligence brings along a certain set of advantages, a set of disadvantages also follow that businesses must consider from a holistic perspective.
Read more: Trends in Big Data Analytics: Forecast for 2023
Data Collection and Artificial Intelligence (AI)
AI systems employ voice recognition and use machine learning to train the systems and understand voice requests. However, what's more important, is that it is also used to design a database that stores the data concerning the person speaking to better offer the kind of requests.
These voice engines are used to create an extensive database with users' interests, likes, and dislikes. On the contrary, it also ties the data directly to the user and, by default, assists in building a solid database about the user.
In most cases, data plays a vital component for companies that are behind these applications’ business models. While they are licensing the technology to use by the company, they are also providing them with other forms of revenue to sell the data and related analytics.
Organizations behind different types of AI apps contain substantial business and consumer user value. The data collected from the engines are often sold or resold, enabling businesses to meet their own goals. And we, as users, deliver a wealth of data to the organizations, either anonymously or with our knowledge.
Many companies are creating their version of a stock photo library of AI-created images to sell to magazines and newspapers, which use stock photos to enhance what they publish. The existing systems use AI to design their knowledge base by scouring the data and using the user's request to collect more information to study their preferences, thereby creating an AI-driven response. It assists in delivering good results to the users and creating more valuable insights for the company.
It is, therefore, vital for users to use software or tools that offer clear terms of use and also take caution in what they share with other companies about themselves or their families.
Read more: A Critical Overview of Big Data and Bigger Dilemmas for Enterprises
The Other side of Artificial Intelligence
A machine does not require breaks the way humans do. This is one of the significant reasons that separate artificial intelligence from the rest. The AI systems are programmed to work for long hours and are capable of continuously performing without getting distracted. This is one of the major benefits for humans, as AI systems help in designing an efficient operations framework for organizations. However, their efficiency can often be affected by many external factors, such as biases or security thefts. While AI does offer several advantages, it has a few disadvantages, which are mentioned below:
Artificial Intelligence (AI) is Expensive to Implement
For any organization, the initial set-up for artificial intelligence requires a high investment budget compared to companies that invest in AI frameworks, which involve the latest hardware and software. Additional costs are also likely to be incurred to train the existing as well as new teams, thus equipping them with skills to utilize the AI systems. All this makes implementing and maintaining generative AI tools and systems expensive. But it is equally true that the high cost that AI comes with equally mandates high maintenance. It requires huge costs to implement safety measures for the complex machines to revert any data theft. Apart from the installation cost for the AI systems, it also requires repair and maintenance costs. The software programs require frequent upgradation in order to cater to the needs of the changing environment. The cost of procurement for the systems is equally high.
Artificial Intelligence (AI) Lacks Creativeness
As AI systems majorly make predictions based on a set of algorithms that are fed to them, the systems often lack creativity, specifically in the content marketing field. While AI systems are advancing over time from inputs and experience, they still cannot think outside the box to generate creative approaches to any task.
Read more: The Next Tech Time Warp: How Will Artificial Intelligence Possibly Change the World?
Artificial Intelligence can never Replicate Human Efforts
No matter how smart a decisive becomes, the system can never replicate human efforts. While machines are rational and very inhuman, they do not possess any emotions or moral values. And organizations cannot inculcate these values in AI systems. The systems do not know what is ethical and legal, and due to this, they cannot develop any judgment-making skills of their own. The systems follow the commands fed to them and perform the tasks as instructors, and therefore, the judgment of right or wrong is zero for them. If the system encounters any situation that is unfamiliar, they perform the task incorrectly or breaks down in such situations.
Artificial Intelligence cannot Understand Emotions and can lead to Biases
Artificial intelligent devices and systems possess the qualities to work faster and without a break; however, they cannot evaluate emotions while arriving at a decision. These systems remain highly rational and practical. This is the reason why AI systems find it challenging to convey emotions while interacting with customers, as emotions are considered a vital element in sales and marketing to convince a customer to make a purchase.
AI Systems cannot Implement Ethics
Artificial intelligence systems are not capable of processing human emotions as well as feeling them. It is challenging for the systems to incorporate ethics and morality into these systems. Advanced versions of AI, including the theory of mind or self-awareness, if achieved, are likely to only implement ethical behavior in the systems. However, such systems are currently on paper, and the framework for them is only partly achieved. For organizations, it will require a long way to think about implementing these ethics in their AI systems.
Read more: 2023 Outlook: Ways Marketing and Advertising will Change for the Better
Final Thoughts
Everything in excess is always dangerous, and the same case can be applied to artificial intelligence. AI incorporated the science of making intelligent machines, which makes it significant. AI and robotics are enhancing the way we think and explore new horizons. And as we know, necessity is the mother of all innovations, and so is AI. We humans today are aware of what we need and are getting increasingly better at defining our wants and transforming this into reality.
Artificial Intelligence holds massive potential to design a better future to live in. But the most important thing to ensure is that artificial Intelligence (AI) is not being used excessively. While there are advantages and disadvantages of AI, its impact is undeniable across the global industry.
Soon, AI will assist in transforming every operation so rapidly that we will witness major changes and innovation. With the simulation of human intelligence and process by machine learning, organizations are designing systems that include learning the acquisition of information and regulations for employing them. These rules enable them to reach definite conclusions and self-correction.
And there is no doubt that technology lies at the core of development and growth. But a small mistake can lead to disruption or destruction.
With a presence in New York, San Francisco, Austin, Seattle, Toronto, London, Zurich, Pune, Bengaluru, and Hyderabad, SG Analytics, a pioneer in Research and Analytics, offers tailor-made services to enterprises worldwide.
A leader in the Technology domain, SG Analytics partners with global technology enterprises across market research and scalable analytics. Contact us today if you are in search of combining market research, analytics, and technology capabilities to design compelling business outcomes driven by technology.
