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Who is Better at Building Relationships



Who is Better at Building Relationships

Humans vs. AI: Who is Better at Building Relationships

Artificial intelligence (AI) has the potential to build better relationships than humans. 

This revolutionizing technology has been around for quite some time now. However, it has only been realized lately as to how important AI could be crucial for humans. The ability of AI to mimic humans using algorithms, and learn from experiences over time, is opening avenues for this technology for building relationships with human beings.

How Humans Are Building Relationships


Source: Very Well Mind

As humans, we have the tendency of building relationships with only a select few. We try to make sure that unwanted and irrelevant people are out of our lives. While restricting our relationships to a few people, we make sure that we build quality relations with those who really matter to us. However, the same approach in business parlance may not be ideal and can backfire. Despite knowing this, the fact still remains that we lack the ability to maintain cordial relationships with our customers at all times – no matter how much we may want to do that. And this happens due to several reasons, such as different time zones, language barriers, dearth of staff, etc.

How AI is Building Relationships

AI has begun interacting with its users and, as a result, it is building its own relationships with them. AI is primarily being used to interact with customers or clients in spaces where human interaction can be easily substituted. An excellent example of AI building relationships with human beings are automated chat-bots that a lot of companies are using to communicate with their customers for, let’s say, answering FAQs (frequently asked questions). Such systems use AI technology and involve human experts only when it’s absolutely required.

Can Humans and AI Build Better Relationships?

With the invention of Emotional Intelligence (EI), the field of AI has received a tremendous boost, resulting in more quality interaction with humans. EI not only creates a better understanding between the bot and the human, it even helps AI complement human effort in various aspects of life. AI with the help of EI Emotional Intelligence can now do the previously impossible.


Unlike human beings, AI tends to not discriminate because of personal biases (though there are instances recorded, but developers are working to eliminate them). AI starts building a relationship with everyone. The chances for manipulation of AI’s ability to make decisions and falsification of the algorithm that it follows are extremely slim.

However, building relationships with AI has its own set of challenges too. Current AI lacks a conscience, which makes it incapable of deciding whether its factually correct decision or response is ethically correct or not. AI also lacks the value of being self-aware, forcing it to make decisions based on algorithms that were ultimately designed by humans.

According to researchers, AI still has several features in store for humans to benefit from. While some of these researchers believe that AI may totally eradicate the need for human relationships, others feel that the enhancements in AI would only lead to better and improved relationships overall.

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How Businesses Can Automate Root Cause Analysis (RCA) With Machine Learning



How Businesses Can Automate Root Cause Analysis (RCA) With Machine Learning

In the event of a severe incident for your business, you need to analyze what exactly changed (the root cause) to understand its impact.

Using machine learning for root cause analysis can help identify the event that caused the change quickly and easily.

Things can sometimes go wrong in your business’s daily operations. It can be a minor issue, such as a system outage lasting for a couple of minutes. Or it can be something severe as a cyberattack.

Generally, such events result from a chain of actions that eventually culminate in the event. Identifying the root cause is the best way to solve the issue. But manual root cause analysis takes time and often doesn’t provide the exact cause of a mishap. Using machine learning for root cause analysis can automate the process, helping identify the underlying cause quickly and with higher accuracy.

Power of Machine Learning for Root Cause Analysis

To understand why an issue occurred, you need to identify the root cause. But root cause analysis can often be complex and provide inaccurate results. Using machine learning for root cause analysis helps solve this issue.


Log Analysis

Using machine learning for root cause analysis can help zero in on the exact location of the problem. You don’t have to scroll through infinite logs to identify which components were impacted and when. The machine learning program can automatically and quickly find the root cause by analyzing a given log data set. 

Moreover, the machine learning program can even predict future incidents as more and more data is available. The program compares real-time data with historical data to predict future outcomes and warns you of any unwanted incident beforehand. This will help improve your incident response, reduce downtime and improve productivity.


Benefits of Using Machine Learning for Root Cause Analysis

There are many benefits of using machine learning for root cause analysis. It can help teams take the right action at the right time, minimizing your losses. Some of the benefits are discussed below.

Reduces Costs

The cost of solving the issue is reduced as your teams don’t have to guess and work around blind spots. Machine learning tools locate the exact line of code responsible for a performance issue, and your team can start working on fixing it right away.

Saves Time

The time spent fixing the issue is significantly reduced as it helps solve business pain faster by locating the cause quickly and accurately.

Provides Long-Lasting Solutions

Machine learning tools provide a permanent solution for your problems and foster a productive and proactive approach.

Grows Your Business

Using machine learning for root cause analysis helps improve the efficiency and productivity of your organization, which eventually leads to business growth.


No system is perfect. Incidents will happen, no matter what. But what you do afterward is in your control. Root cause analysis should be done as soon as possible. Using machine learning for root cause analysis not only improves your incident response, but over time, it can also help prevent incidents from happening in the first place.

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