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How Does Artificial Intelligence Help In Decision Making

Artificial intelligence has significantly changed the way we interact with technology. In short, AI simplifies our lives. Although some may not realize it, artificial intelligence has become part of everyone’s daily lives. An overview of how artificial intelligence can help in making decisions can be found here.

Amazon Echo and Google Homeowners know how convenient these AI-powered devices are, especially given their ability and accuracy. During voice searches, AI can deliver results and enhance customer experience by seamlessly processing voice commands.

Statistics related to AI and machine learning

These chatbot statistics show the extent to which artificial intelligence has grown.

The popularity of voice assistants like Siri, Echo, and more has grown so much that 97% of mobile users use them.
Because artificial intelligence offers a competitive advantage for organizations, 80% are considering using AI for customer service.
AI is considered a critical component of their data strategy by 61% of marketers.
Machine learning (ML) is expected to aid business decision-making for 65% of companies implementing it.
Chatbots will be used to automate 90% of customer interactions by 2022.

Examining AI’s abilities to make decisions

To determine whether or not artificial intelligence is trustworthy for making decisions, especially when the stakes are high, we need to first know what artificial intelligence can do today and know the benefits and risks of AI.

  • AI is better at handling multiple inputs.
    Humans are less reliable at handling multiple factors at the same time when making complex decisions when compared to machines. Data can be processed by machines in minutes while valuable insights are delivered, something which would take humans a very long time.
  • Speed up the decision-making process.
    In all fields and locations, things are always moving at an accelerated rate. With dynamic pricing, you can optimize your margins for eCommerce or any other industry.
  • Detect patterns
    Human analysis may not be easy to detect when it comes to buying patterns. These patterns can be spotted using AI-powered analyses, and businesses can benefit from the discovery of these patterns.
    In order to better understand a customer’s buying patterns, you should align your products based on those patterns that show the customers’ needs. A simple prediction tool can easily surpass humans in this aspect, and AI is predicted to grow hacking in the future.
  • Algorithms are immune to decision fatigue
    In contrast to humans who tire after hours of making decisions and processing data, you won’t face this concern with AI.

Their ability to make repeated decisions without tiring over time ensures the quality of the decisions they make. Exhaustion can lead to poor decisions that can be mitigated.

How difficult is it to trust AI decisions?

How difficult is it to trust AI decisions

Artificial intelligence is already deeply embedded into many components of our lives. However, it can still be subject to errors, especially if given wrong information or inadequate training data. Let’s look at some challenges AI currently faces.

1. Human values

Artificial intelligence is becoming more and more capable, making humans concerned about its “human values”. When people first heard about autonomous cars, they were excited, but then their decision-making process began to question how autonomous cars could cope with challenging situations.

Imagine a truck coming toward you at a dangerous speed. When a driver swerves, this can cause a catastrophic accident.

  • How would an autonomous vehicle act?
  • How would it make a decision?

These are complex questions. Finally, the bias of the programmers could be a determining factor, and this can lead to a rapid erosion of trust in AI decisions.

2. Transparency

Trust is based on transparency. The trust issue will always remain until businesses and organizations are able to be fully transparent, and that is how things have always been.

Likewise, people are always curious about the hows and whys of AI systems. The ability of AI systems to arrive at certain conclusions and even provide personalized recommendations is amazing. Nevertheless, there will always be concerns since they cannot (for now) explain how they can derive a particular result.

The military field, which is high-stakes, has focused on the issue of trust as well. It is perhaps for this reason that Defense Advanced Research Projects Agency (DARPA ) launched several projects aiming to explain, as close as humans could, how an AI reaches a particular conclusion.

Another company wants to use AI machines to better manage their workflow and give accurate reports on their performance under various conditions.

3. Accuracy autonomy

Artificial intelligence makes decisions based on predictions. Most AI systems’ decisions are accurate when they are 95% or higher. In terms of essential daily AI uses, that’s impressive and indeed reliable, but it would be much different when it comes to high-stakes applications. Should machines be given higher autonomy?

4. Are there ways to boost AI decision-making?

Currently, AI can handle mundane tasks, allowing employees to focus on more important tasks. However, with all their capabilities and the benefits they bring, would it be wise to trust AI decisions when the stakes are high? It’s unclear. Here are a few ways AI can make decisions better.

  • Customize AI for specific purposes
    Artificial intelligence is yet to become a reality. Team members responsible for designing AI should collaborate with those who are familiar with the implications of AI within the organization.
    The biggest mistake is to only focus on making technology and algorithms more advanced without considering the needs of those who will be using the insights. Designing an artificial intelligence system must keep the user in mind.
  • Facilitate data exchanges between organizations
    Essentially, AI runs on data, and they base their decisions on that data. Most organizations have their IT infrastructures built by different individuals or teams over time.
    Thus, we end up with data that is fragmented and unrelated. In order to improve the organization’s artificial intelligence, it would take a unified data architecture.
  • Establish strategic partnerships
    In order to benefit from AI trends in eCommerce, you should work and partner with firms that have proven their proficiency with navigating the AI system from product design to shipment.
    Technically skilled business people who understand AI and are willing to apply it in decision-making will be able to generate positive results for your business and help you overcome any obstacles.
  • Invest time in training.
    The accuracy of AI decisions depends on the data used to train its system, so organizations must unite their data to feed AI systems. Lastly, you ought to consider the data’s quality in order to avoid bias.
    As opposed to solely using data applicable to the majority, taking into account data from minorities for a complete representation to support concerns about accuracy and inclusion.
  • Keep track of AI regulations.
    Do not abandon the idea of an AI “watchdog” that could supervise, regulate, or scrutinize audit algorithms, which is particularly helpful when it looks like there is any possibility of bias.
    Prior incidents of people being mistaken for AI systems have occurred, some of them were just nuisances. Other incidents had a greater stake.

In some cases, AI errors led to loss of jobs, detentions, and missed opportunities. Third-party regulators have challenged such decisions. For those new to this technology, there are podcasts like AI Nation, CNA, and Apple that will teach you more about AI regulations.

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