Artificial Intelligence

Artificial Intelligence technology has received particular attention recently. This technology enables machines to learn and “think.” AI can have a positive impact on economic and social change. However, this innovative technology has some problems.

What is AI

AI is a field of computer science that enables computer systems to learn and perform tasks typically associated with human intelligence, such as speech recognition, decision-making, and vision.

There are three types of AI: artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial superintelligence (ASI).

  • Specialized Artificial Intelligence (ANI): ANI is classified as “weak AI” because it specializes in only a narrow range of parameters or situations, such as voice recognition or self-driving cars.
  • Artificial General Intelligence (AGI): AGI is considered a “strong AI” because it operates at a high level similar to human intelligence.
  • Artificial Superintelligence (ASI): Although this type of AI is not currently being developed, ASI refers to a machine with superintelligence, i.e., more intelligent than humans.

Two essential technologies—machine learning (ML) and deep learning (DL)—are required for AI to work effectively.

ML and DL create the environment in which AI functions. ML is a set of tools and algorithms built into computers that “learn” or use existing data to generate accurate predictions. DL is an automated feature in machine learning that enables machines to detect patterns and “think” about classifying information. Next, I explain the top 5 AI tools most commonly used today.

Chatbots

“Chatbot” is a program that automatically carries out conversations.

In recent years, with the development of artificial intelligence and natural language processing technology, various chatbots have appeared in web services. They are expected to be communication tools that connect “users and companies, ” like customers and employees.

There are two main types of chatbot conversation mechanisms.

Conversational AI

In conversational AI, the chatbot first presents options. Next, the user selects the item corresponding to the question from the options.
Then, the chatbot presents further options. Finally, the user selects an option.
After several iterations, the chatbot eventually provides an answer. Recently, some services have explained how to address the problem in videos.

The advantage of conversational AI is that it allows you to answer based on options, so you can expect an accurate answer without deviating widely from the user’s intent. It is suitable for responding to inquiries that require detailed information on events and issues, such as “response to system and equipment troubles” and “operation methods.”

The problem is that you may not be able to answer complex questions because the question options are limited. On the other hand, building and maintaining a “QA list” of questions and answers required to answer takes time and costs.

Generative AI

This chatbot uses artificial intelligence to select answers that are statistically likely correct. Its mechanism automatically learns from conversation logs and improves the correct-answer rate and conversation accuracy.

It can respond to more advanced and wide-ranging inquiries than conversational AI. Therefore, the human cost for operators and others can be reduced.

Artificial intelligence needs to be trained on data in advance. A vast amount of data input is required for natural conversations. If the machine learns incorrectly, it will likely give incorrect answers or engage in inappropriate conversations.

Content creation

AI is a valuable resource for content creation. For example, AI and SEO (Search Engine Optimization) help digital marketers be more productive with on-page and off-page SEO. AI can create various things, such as emails, blogs, e-books, and landing pages. However, AI alone cannot make all of these things.

Creating these requires human instructions. By providing prompts to the AI and giving it detailed instructions about the kind of product the person wants to make, humans can create more accurate products.

AI-generated content is valuable in many areas, but it is beneficial for content creation for the following reasons:

  • Time efficiency ️- Imagine producing an incredible amount of content in a fraction of the time it takes a human writer.
    AI-generated content is about speed, allowing companies to meet tight deadlines and keep content pipelines flowing smoothly.
  • Cost-effective creation – By automating content creation, companies can reduce the cost of hiring and maintaining a team of writers. The result is a cost-effective solution for creating top-notch content at scale.

While the appeal of AI-generated content is undeniable, it is essential to recognize its limitations and potential pitfalls.

  • Lack of human touch—AI-generated content often lacks the human touch and creativity that make it genuinely engaging. Even though AI-created sentences may be technically correct, they lack the nuanced emotion, humor, and emotional connection that human writers infuse into their work.
  • Ethical issues: AI-generated content is fraught with moral concerns.
    Issues such as the spread of misinformation, bias in content creation, and the impact on employment opportunities for human writers need to be addressed. For example, AI-generated political content can inadvertently perpetuate prejudice and misinformation with potentially harmful consequences.

Grammar checkers and rewording tools

Grammar and spelling are essential in writing content. Even if something includes important information, it will look poor if the content contains grammatical or spelling errors. In addition to quality, grammar and spelling play a significant role in clarifying your main points and topics. And the good news is that AI has the magic to perform grammar and spell-checking. Top-grade AI tools can not only check grammar and spelling but also suggest replacements for errors.

Video creation and editing

Generative AI, which uses AI technology to create videos, images, and text, has become a hot topic. Using the video generation AI service, you can make simple videos using only text data. Also, AI-driven video editing is a technological evolution that can be called a new revolution in video production. Traditional video editing tasks require a lot of time and effort, but with the advent of AI, they have become much more efficient.

Specifically, AI can analyze a video’s content and automatically perform repetitive tasks such as optimal cuts, trimming, and color grading.

Realizing efficient video production

A feature of AI video editing tools is that anyone can easily create high-quality videos, making it possible to produce compelling content quickly, even without video editing expertise. It’s now possible.

For example, some tools use AI to automatically edit videos, allowing users to complete videos within 10 minutes by simply entering materials and text. Another appealing feature is that anyone can easily create a video with only basic editing.

Possibility of improving quality

One benefit of AI-powered video editing is the ability to analyze video. AI can extract and explore videos and images, enabling it to pick out specific scenes or people.

For example, AI can analyze videos of sports matches and perform play analysis. This can be used in fields beyond sports, and by registering the faces of performers who have appeared in past videos, AI can automatically recognize and extract performers’ faces in videos. This enables more advanced analysis, and AI can improve video quality by making adjustments based on the analysis results.

Videos are likely to be monotonous.

Video editing using AI is likely to result in monotonous videos. Since videos are generated from learned data, many tend to share similar patterns and styles.

If the same person is giving instructions, that person’s preferences and styles will be strongly reflected, which can lead to a lack of diversity. Additionally, if the video becomes monotonous, viewers may quickly grow bored, and the content may feel stale.

Unable to specify detailed conditions

Video editing using AI has the disadvantage that it is challenging to specify detailed conditions. For example, it becomes difficult to fine-tune the atmosphere of a video or place specific effects. AI cannot yet understand subtle nuances and make edits based on them, as humans do.

However, it is suitable for producing monotonous explanatory and advertising videos, so it is essential to consider using AI according to the requirements.

Image generation

Image generation AI is a technology that automatically generates images. It is also known as a deep learning technology, a machine learning method.

In recent years, high-quality images have become required in various situations. However, it is not always possible to obtain completely original photos that meet these demands. For example, there may be cases where only out-of-focus, blurry image data is available. Additionally, for historical materials, many cases have no color photographs and only black-and-white photographs, and some may have only rough sketches.

In such cases, preparing high-quality image data by performing specialized and time-consuming image processing or drawing illustrations while solidifying the shooting concept and then taking the photos is challenging. However, recent advances in AI technology have made it possible to create high-quality images even from insufficient data.

Generative AI offers many benefits, from streamlining business processes to generating new ideas.

Lowering technical hurdles—The introduction and use of generative AI do not require specialized technical skills or in-depth knowledge, making it accessible to many people. By reducing the hurdles and opening the door to exploring new ideas and projects, it can be used in diverse fields such as text generation, music creation, and design.

Additionally, since generative AI emphasizes intuitive operability, it can be expected to significantly reduce the time and cost of educating and training employees and team members. In other words, companies and individuals can focus on creative and valuable work by implementing generative AI.

Copyright issues

Copyright issues may arise when using AI-based image generation technology. For example, if a copyrighted image is used in the training data, the AI that generated the image may also be copyrighted.

Additionally, humans may misinterpret images generated by AI, which may affect the accuracy of the information. To solve this problem, the legal system must be improved, and the use of AI must be considered ethically.

AI problems

AI has created many positive effects. However, new problems are emerging at the same time.

  • Decrease in employment – In the future, tasks currently performed by humans may be handled by artificial intelligence. In particular, artificial intelligence will likely become the leading technology in technical jobs such as driving and construction.
  • Risk of information leakage – When using artificial intelligence, networks handle confidential customer information. Although this is very convenient, you need to be careful, as there is a risk of being hacked from the outside or of information being leaked. There have been many cases of cyberattacks that exploit AI’s learning capabilities to infiltrate systems at an overwhelming speed. Only AI can likely counter attacks using such technology. It is necessary to utilize security systems equipped with AI and take security measures with multi-layered defense.
  • Difficult to manage risk –  As more companies leverage AI, the need for risk management also increases. If the AI system you introduced malfunctions, all related operations could stop, causing significant losses to the company.

Before introducing AI, it is crucial to understand the potential risks and causes of problems, the extent of their impact, and how to address them. If a company lacks human resources with specialized AI knowledge, it will be challenging to address problems.

The future of AI

The future of AI is innovation and evolution. Technologies such as machine learning, neural networks, and deep learning will continue to evolve and accelerate, as will how people search and get answers, through their integration with natural language processing and robotics.

AI has unprecedented possibilities, such as autonomous driving and unmanned stores. However, challenges such as ethics and privacy remain, and regulation, transparency, and accountability are becoming increasingly important. Future social development will focus on how well humans can incorporate AI into society. The technology landscape will change from healthcare to digital marketers using content marketing.