Threats and opportunities of AI in business (part 1) | AI in business #2

Will artificial intelligence soon be able to read our thoughts? Will the existence and functioning of AI serve to meet human needs to its full potential? Or, increasingly out of our control, will AI seek to independently control the choices we make? The questions we just asked sound like the introduction to a sci-fi essay. However, they are quite real doubts and problems faced today by the developers and early users of the most advanced AI technologies.

Threats and opportunities of AI in business – table of contents:

1. Threats and opportunities of AI in business
2. Cybersecurity and cyber threats to artificial intelligence
3. Safer with AI
4. Safety Concerns
5. Access to information and AI
6. Widening Access
7. Credibility issues
8. Summary

The hopes and threats of AI in business

Applying artificial intelligence in business raises great hopes. That includes new markets and products, innovative services and ways of contact with customers. But it also generates fears concerning not only the security of sensitive data of the company and its contractors but even the further existence of entire business branches.

In today’s article, we’ll look at the threats and opportunities of AI in business. We will focus on the pros and cons of AI in the following areas:

• security
• access to information

In the following text, we will address the threats and opportunities of AI in business operations as they relate to the cost and present and future jobs.

Cybersecurity and cyber threats to artificial intelligence

The area of security in the digital world is one of the most sensitive topics being addressed concerning artificial intelligence. We entrust it to analyze, create, and even decide on increasingly crucial issues. Therefore, we must be aware not only of the opportunities for business development but also of the risks associated with the application of AI.

Safer with AI

Thanks to the use of AI, we can reach for improved security based on advanced user recognition technologies, popular for example in online banking security. Their essential components are systems:

• voice recognition, which is part of NLP, or Natural Language Processing
• image recognition (computer vision), especially face identification

The key sector of employing artificial intelligence to improve security concern analyzing the monitoring of events such as concerts or major sporting events. AI can therefore greatly facilitate the operation of companies involved in the protection of mass events. It will not only shorten the time of security control by comparing the presented document or ticket and the face of the person presenting it. Artificial intelligence enables detecting the presence and locating individuals who could potentially pose a threat, as well as those behaving contrary to security rules.

Another major opportunity related to the development of AI-based security is the monitoring of smart properties or smart homes. Without the help of AI, these would be vulnerable to attacks by hackers who, by breaking into the system, could enter the home unhindered. With AI, real-time monitoring is possible, detecting actions that could disable it in a much more sophisticated way than, say, antivirus software running on a computer.

An even more technologically advanced and very rapidly growing industry is artificial intelligence enabling unmanned stores. It usually combines advanced monitoring with the operation of mobile applications of logged-in users. Thanks to such solutions, it is possible to recognize a customer visiting a store and unnoticeably scan goods purchased and collect payment for services. They are also popular in other sectors, such as unmanned hotels.

Safety Concerns

However, these kinds of AI solutions involve certain risks and threats that companies have to consider. The most serious concern is leaks or theft of detailed identification data collected by the service provider.

There are also risks associated with the lack of brand-new AI laws and regulations. It may result in unpredictable consequences of the misuse of user data by companies storing it to uncontrolled surveillance by government authorities.

Moreover, there’s yet another profound concern involving the safety of AI in neurotechnology. In other words, the potential threat of building interfaces that enable direct brain-machine communication by reading brainwaves.

Access to information and AI

What raises the major worries about connecting the human brain to artificial intelligence also raises the greatest hopes about access to information and the speed of its processing.Solutions that can read brainwaves already allow for artificial speech synthesis or drone control. Thus, interfaces featuring the operation of machines or medical tools with thoughts are already at hand.

Widening Access

Ease in handling is a colossal convenience that lets any person seamlessly access information and education. One of the most accessible interfaces for the average user is voice search using naturally asking questions and similarly receiving answers. It makes it so that we don’t have to know specialized terms or advanced search engines to find the products or services we are looking for.

The next milestone in AI-assisted information access is image search. Few people realize how complex this task is. However, its use means tangible benefits for business, not least because it significantly reduces the role of location. With image search, you can search for similar goods using a photo, without the intermediary of a product description provided in a specific language.

Credibility issues

Unfortunately, there are also inevitably risks associated with the field of AI-assisted access to information. If artificial intelligence is to answer our questions accurately, we must be sure that it draws information from reliable sources. This is where the problem of AI learning techniques emerges.

We can divide it into three areas:

• collecting the data on which artificial intelligence is taught,
• data selection, i.e. the problem of verifying the veracity of information and rejecting, for example, fake news,
• applying the data, i.e., the conclusions drawn by AI from the set of data made available to it.

The reliability problem can be illustrated with a simple example. Imagine that an AI learned what cats look like from a set of pictures chosen incorrectly, in which all cats were black. By which it concluded that all cats are black.

Translating our problem into the realm of business, AI used to make investment decisions could learn from a set of mismatched financial data. For example, on one where the value of company A’s stock is rising all the time. So the AI defined it as a stock whose value is constantly growing, so such an investment has no risk.

Summary

The opportunities of AI in business primarily include:

• digital security
• advanced monitoring that allows not only to prevent dangerous situations during mass events but also to operate unmanned stores
• quick access to information
• intuitive voice and image search

In contrast, the primary risks we discussed above take into account:

• theft and misuse of sensitive customer and business data
• the potential risks of using brain-machine interfaces
• problems with the reliability of the answers provided by AI

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