Artificial Intelligence: Key Challenges and Opportunities

Chatbots responding to your queries on a website.

Robots serving your dinner at a restaurant.

IoT connecting devices to create a self-operating network

These are just a few practical applications of artificial intelligence. The scope and the development of this technology is immense. However, as more and more organisations are exploring the opportunities of AI technologies, they are also tackling the challenges that the new technology brings.

Challenges of AI

AI technology is developing at a rapid rate. At the same time, developers are facing challenges that have almost become roadblocks in AI’s development path. A few of the challenges of AI are:

Provability

Over the years, we have seen AI demonstrate great capabilities. However, AI scientists are finding it difficult to “prove” how AI makes decisions and predictions. It is difficult to explain the math behind the predictions. AI should become transparent, explainable, and provable.

Data privacy and security

Traditionalists are sceptic about this new technology as it opens up access to huge volumes of data, be it organisational or personal. AI applications cannot make the right decisions without huge volumes of data. Because of this, the data becomes vulnerable to identify theft and data breach. The development of “Federated Learning” may help build AI applications without compromising on data confidentiality and security.

Algorithm bias

AI applications simply follow the algorithm to derive the results. So, whether it is fed with good data or bad data, it churns out the results. For example, certain applications are used to evaluate the job fit of a prospective candidate for a job role. Based on the algorithm, the application will give you a list of possible candidates. So, imagine you have used a criterion to weed out candidates who’ve been granted bail. The algorithm doesn’t check why there was a necessity for the bail, but simply remove the candidate from the list. Similarly, it can bring in bias based on colour, gender, nationality, and other parameters based on the algorithm created.

Data scarcity

In the digital age, organisations are generating millions of bits of data. However, most of these data sets may be irrelevant to the AI application or may need to be labelled. There are scores of unlabelled data, but very less amount of labelled data. So, every time an algorithm is created, the scientist needs to identify means to label the data. This process can be time consuming. Also, if the data labelling process is not consistent, then it could lead to inconsistencies in the final results.

The way ahead – How to face AI challenges?

With the AI taking the world by storm, the only way ahead is to work with the challenges and find effective solutions. We need to find ways to label and interpret data to ensure that the right data is fed into the algorithms. Data analysts and AI scientists need to find ways to ensure the highest level of data confidentiality. At the same time, they should also look for ways to overcome bias in the algorithm creation process.

How Companies Face Challenges?

Companies need to face the AI challenges head on. The data of millions of users is at stake and the AI predictions can bring about huge changes in the system. So, while making the most of the AI opportunities, organisations should also be careful to prevent identity theft and data piracy.

Who can Join the AI course?

If you are a graduate or a working professional interested in building a career in this emerging field, you can take up the course. The applications of artificial intelligence are being used in various sectors such as healthcare, IT, education, finance, retail and more. So, even if you are not from a technical background, you can learn Python coding and join the course. However, if you are from a software background, then you can join the course and start your career in this field.

What are the Job opportunities in AI?

As we explained earlier, AI finds applications in various sectors. Also, many companies are now investing in artificial intelligence. So, the number of job opportunities is quite high. After completing a course in artificial intelligence, you can join an organisation as a software developer, AI architect or AI engineer. You can also specialise in deep learning or machine learning and build your career in these sub-domains of artificial intelligence. The average salary package of an AI professional is around INR 6 lakhs per annum. Professionals with more than 5 years of experience can earn anywhere between INR 15 to 20 lakhs per annum.

Corpnce offers one of the best AI Courses in Bangalore

We offer professional courses for graduates and working professionals. At Corpnce, we follow a project-based training methodology to help students learn by practice and application. The projects are designed to give hands-on experience to students that will help them be work ready from day one. To know more about our AI courses in Bangalore, contact us.