The AI Impact on Industries: Major Sectors

These five industries are where AI use cases play a critical role in enabling certain changes.

First, the financial sector. This highly sensitive and crucial industry in the economy can significantly benefit from AI. Machine learning methods in finance, such as regression or neural networks, can detect data patterns that allow for process automation, risk prediction, pricing, or fraud detection. Specialized machine learning techniques, like deep learning, can learn from historical financial transactions. As a result, innovations are emerging in algorithmic trading, anti-money laundering efforts, and chatbots.

For example, tools created by NetGeist for financial sector businesses include 24/7 chatbots that respond to basic questions such as checking customer bank balances, pending payments, upcoming deadlines, and more, integrating text-to-speech and vice versa technology.

AI application can also retrieve various customer data, such as income and expenditure history, to calculate credit risk scores that can be much more accurate than traditionally calculated results.

Banks also use AI to offer personalized product recommendations to customers based on their transaction history and spending patterns. NetGeist’s service integrates an AI tool that can automatically generate a personalized financial or insurance plan by analysing customer behaviour.

This ensures greater efficiency and reduces the likelihood of illicit funds entering the system. AI-driven oversight can also help ensure compliance with regulations by flagging transactions that may violate certain rules.

The second sector is healthcare. Medicine is undergoing a revolution as new opportunities arise to improve diagnostics, personalize medicine, and perform predictive analysis.

One successful example of AI impact in industry is medical imaging. Currently, an AI-powered automated detection tool can assist emergency physicians in diagnosing COVID-19 based on lung ultrasound imaging results.

Predictive analytics can be used to create personalized treatment plans, with AI making them more data-driven by analysing medical history and real-time information. NetGeist offers a tool that enhances communication by converting important information from text-to-speech and vice versa, improving services for patients with visual or hearing impairments.

The third area is government. Here, several sectors can benefit from AI as an effective tool. First, digital tools powered by AI can be used to improve public services for citizens, such as various digital self-service models.

In political processes, the AI impact on industries can be observed through its ability to generate more efficient political insights, such as analysing societal impact or resource utilization.

It can also be used to initiate new projects and changes. For instance, AI can generate information about real-time bus occupancy and its fluctuations, helping to develop effective transport management systems.

Another sector seeing significant AI impact is retail. Online shopping is thriving, and AI solutions are being integrated. Based on search history, retailers can offer personalized recommendations to customers, increasing sales and improving customer experience. Chatbots can answer questions faster and solve issues, while new technologies can help optimize internal processes like inventory management.

The final sector where AI integration is significant is education. As in many other industries, internal processes are being improved and sped up. In this case, it includes automating student achievement tracking, progress, and analysis, which allows for a better understanding of individual student progress.

Data analysis can also help tailor educational materials to each student’s needs based on their performance, something a single teacher may struggle to do in a large class. Additionally, real-time monitoring through tasks helps assess how well students understand lesson topics and improves efficiency during lessons.

Moreover, an interactive learning environment is created, with augmented reality technology enriching lesson content. AI also helps create a more supportive environment for students with special needs.

Final Word

Considering these five industries, we can observe the significant AI impact on industries, driving innovation and addressing challenges in unique ways. It remains crucial that deliberate decisions are made in these important areas to ensure that AI’s implementation brings benefits rather than losses to these industries.

If you are interested in this topic, we suggest you check our articles:

• Reinforcing Cybersecurity with AI
• Customer Service in the Age of AI
• New Obstructions in AI for Mental Health

Sources: Datacamp, Forbes, Keymakr, NetGeist, TechTarget

Top AI Headshot Generators

One of important aspect is that AI has made significant progress, and from previously illogical and incoherent images, it can now generate highly refined photos. By providing a simple existing image, you can achieve the desired result. Thus, it is an excellent tool for businesses of all sizes to create a solid image or represent their team.

Not only does this save time and resources, but it also plays a role in privacy protection, as real team photos are not being published. When choosing an AI headshot generator, there are several factors to consider. First, speed. In this case, free tools are often the fastest.

Second, accuracy or realism. While the quality of results depends on each individual case, some tools are known for their high accuracy, while others might produce more ethereal images. Finally, the intended use – whether it’s for large companies that require various additional features or smaller businesses needing only basic functionality at a good price.

1.      Portrait Pal

This tool uses advanced machine learning technology, making it an excellent choice for those seeking high-quality results. Original photos are analysed using a deep learning model, namely stable diffusion. It is a paid tool that can deliver the final result in 30 minutes without requiring additional editing.

2.      BetterPic

Although the realism is slightly lower compared to the first tool mentioned, for an additional fee, it offers customization options, such as changing clothes, hairstyles, or the photo background.

3.      Aragon.ai

A professional AI headshot generator, whose algorithms were developed by researchers who worked with Meta and Microsoft. It delivers versatile results within two hours. A distinctive feature is that Aragon.ai allows users to input textual comments about the photo, such as background or outfit descriptions.

4.      MyEdit

A good option for those looking for a free tool. Users get 3 free credits per day to generate professional photos. The process involves uploading a photo and selecting 8 preferred photo styles, with suggestions generated within 10 minutes. The generator also includes other tools like background removal, background generation, and converting photos into avatars or sketch/cartoon styles.

5.      PixelPose

Another AI headshot generator, PixelPose is ideal for those seeking exceptional quality. One reason is its modernity, which ensures precise image reproduction and creates a solid overall impression.

6.      Dreamwave

This AI headshot generator offers unlimited background and outfit options, allowing for a wide variety of looks. The photos are highly realistic, but the price is one of the highest on the market. In addition, the price in this app is presented only after uploading photos.

7.      PFPMaker AI

Another free alternative for those seeking a budget-friendly option. It allows users to crop their preferred photos and change the background colour. It focuses on speed and maintaining quality, with the free version offering 90 generated photo options.

8.      HeadshotPro

A simple and traditional photo generator that creates sufficiently professional images. The company offers a team package for creating a consistent image for employees. Generated photos can be edited, but most styles are neutral, making it less suitable for more creative solutions.

9.      StudioShot

This tool focuses not on the number of suggestions but on the ability to refine the generated image through detailed editing. However, this approach lengthens the time it takes to deliver the final result, which can take up to two days.

10.  LightX

An online photo editor with a free AI Person Photoshoot tool that can be used to create business photos. It is very user-friendly, making it perfect for individual and personal needs.

Final Word

The demand for photo generators in the market is enormous. Identifying specific needs becomes a critical factor in choosing the right tool. Some may require a professional AI headshot generator offering high-quality results, while others may find a simpler, more economical tool with basic features sufficient.

Sources: CyberLink, The Hollywood Reporter, RollingStone

How Does AI Create a Music Playlist?

The first to experience this new feature on Spotify were app subscribers in the U.K. and Australia. Now, the AI-generated playlist function is also available to users in the U.S., Canada, Ireland, and New Zealand.

Although still in beta, users can already test out this innovation. The tool works by allowing users to describe the playlist they want to generate, such as romantic songs for a dinner at home, or a party playlist for friends. AI then generates a playlist that reflects the described mood. Notably, the descriptions don’t need to be brief, they can include creative ideas.

There is also the option to refine and further edit the description to improve the playlist. Additionally, the descriptions don’t have to be purely textual – they can be enhanced with visual elements such as emojis, colours, or even references to movie characters to help convey the desired playlist mood.

What Opportunities Does Spotify’s AI Playlist Feature Offer?

One of the main benefits of applying AI to playlist generation is the significantly reduced time spent searching for new music or songs that match a specific mood or theme. The process becomes faster and more efficient, as machine learning immediately suggests songs based on both the description provided and the user’s previous activity history.

Analysing past activity ensures that the playlist is personalized for the user, making it more likely to meet their preferences and expectations. Another key aspect is that AI continuously learns from users’ habits and requests, becoming more accurate over time in generating content.

The vast array of available music also means that AI can analyse large amounts of data to select the most fitting suggestions. This increases the likelihood of expanding one’s musical tastes and discovering new, up-and-coming artists – something that, from a different perspective, benefits the artists themselves by improving the visibility of lesser-known or emerging musicians.

Can We Fully Rely on an AI-Generated Playlist?

One of the important risks associated with AI in various fields, including music, is that its great potential for personalization may lead to a limited perspective. Much like social media algorithms create “filter bubbles,” AI in the music industry could lead to users being confined to a specific musical bubble, where over time they may view music from only one angle, limiting exposure to other genres or styles.

Moreover, it’s important to remember that AI is not infallible – it can make mistakes or misunderstand the deeper contexts of a user’s search or their emotional expression, resulting in playlists that don’t match the user’s expectations.

Additionally, in this version of Spotify, AI will not create playlists based on political messages or descriptions containing terms like “deceptive” or “dangerous.”

Final Word

Artificial intelligence is gradually becoming one of the new age’s DJ alternatives, offering its own generated music playlists. This is yet another tool that enhances user experience and opens new possibilities in the music industry.

Sources: Spotify, TechCrunch, Fast Company

What is Open Source AI?

Open-source AI platforms are software and toolkits that are available to everyone. The source code of these platforms is publicly accessible, enabling users to customize the software based on their needs, collaborate with others, and share improvements.

The growing integration of machine learning into businesses encourages the adoption of these innovations, allowing automation of processes, enhanced data analysis, and the creation of new products. Open-source AI provides an accessible, cost-effective space that doesn’t rely on proprietary systems, making it a popular choice across various fields.

Open-source AI platforms are already transforming many sectors, significantly improving their performance. In healthcare, they are used in medical image analysis, such as X-rays and MRIs. In retail, they personalize customer experiences and integrate chatbots, while in the automotive industry, open-source AI is helping to develop self-driving technologies.

15 Open Source AI Platforms

A wide variety of open-source AI tools exist today. Below are 15 of the best platforms available:

1. TensorFlow

TensorFlow is a highly popular, free, open-source platform designed for creating and training machine learning models. It is used across various industries, including Gmail and Google Photos. TensorFlow is flexible, allowing users to retrain existing models or build new ones from scratch, and it offers a range of instructional videos.

2. PyTorch

PyTorch is a machine learning library that utilizes Python and operates as a one-stop solution for turning ideas into functional applications.

3. Keras

Designed for fast experimentation with deep neural networks, Keras works well with other libraries like TensorFlow. It’s a great choice for both beginners and experts creating new prototype ideas.

4. OpenAI

OpenAI, a leader in AI innovation, offers tools like OpenAI Gym, which are used for testing and developing reinforcement learning algorithms. It’s one of the most popular platforms for research and learning.

5. Rasa

Rasa is used to build conversational AI, such as chatbots and virtual assistants. Its machine learning technology simplifies understanding natural language responses and enables complex dialogue commands.

6. Scikit-learn

Known for its consistency and beginner-friendly nature, Scikit-learn integrates Python and provides numerous machine learning and statistical modelling tools.

7. Apache MXNet

Apache MXNet focuses on being a flexible and efficient open-source deep learning system, capable of handling various tasks. It’s suitable for both research and production.

8. CNTK

CNTK (Microsoft Cognitive Toolkit) is a deep learning toolkit backed by Microsoft, supporting services like Cortana and Azure.

9. Caffe

Caffe excels as a high-performance deep learning system, making it ideal for tasks such as image classification and real-time object detection.

10. Theano

Theano integrates deeply with NumPy and is known for its efficient gradient calculations. This platform allows developers to create new machine learning algorithms and handle large-scale mathematical computations.

11. OpenNN

OpenNN is a C++ class library specifically designed for building and using neural networks, making it a great option for researchers.

12. H2O.ai

H2O.ai is an open-source machine learning platform that supports various algorithms and integrates easily with Hadoop and Spark. It also simplifies the process of building predictive analytics models.

13. MLflow

MLflow is a platform for managing the entire machine learning lifecycle, from data preparation to deploying production models.

14. Shogun

Shogun is a machine learning library offering a wide range of unified machine learning methods, designed to solve large-scale machine learning problems.

15. Ludwig

Ludwig is a toolkit that allows users to train and test deep learning models without writing code. It’s perfect for non-experts who need to train cutting-edge models with minimal setup.

Final World

Open-source AI opens vast opportunities to enhance business projects. It offers accessibility that encourages experimentation and the discovery of the best possible solutions. However, it’s important to note that companies must invest in knowledge and expertise to effectively use these freely available platforms. With the right approach, open-source AI can become a key component in driving business success and innovation.

Sources: Digital Ocean, Telnyx, Medium, GeeksforGeeks, HubSpot, Qodex

In the Shadow of Cyberattacks

Cybersecurity refers to any technology, practice, or policy aimed at preventing digital attacks and mitigating their potential impact. The focus in this field is on computer systems, programs, devices, data, or financial assets.

Meanwhile, cyberattacks can be triggered for various reasons, ranging from minor theft to acts that could be considered warfare. They are intentional efforts to steal, alter, or destroy data and programs by unlawfully accessing a computer network.

An example of a significant breach is the 2023 MOVEit cyberattack, where servers were compromised, and data from more than 2,000 organizations — about 60 million people’s information, including that of organizations like British Airways and BBC — was leaked. Unfortunately, this was one of the largest attacks, not only due to the number of affected individuals but also due to the financial damage and long-term impact.

Another example is the 2014 Yahoo breach, with even graver consequences as over 500 million data were compromised and stolen. The situation worsened when the company concealed the breach until 2016.

The 2020 SolarWinds cyberattack is regarded as one of the biggest information technology security breaches of the 21st century, as it caused severe vulnerabilities in the supply chain and affected thousands of organizations, including the U.S. government.

These examples show the massive damage such attacks can cause, underscoring the urgent need to find ways to reduce the risks posed by these threats.

AI as a Cyber Shield

Traditional cybersecurity relies on manual analysis, which can be carried out by a single specialist, posing the risk of human error. Moreover, such analysis can take a significant amount of time. In contrast, AI can analyse vast amounts of data, recognize patterns, and generate insights based on the data analysed.

One of the key areas is behavioural analysis. For a cyberattack to manifest, malicious behaviour must emerge in a program, which well-trained artificial intelligence — often AI-based extended detection and response (XDR) tools — can identify, respond to more quickly, and alert about suspicious behaviour.

Moreover, AI can not only instantly detect suspicious activity but also respond automatically to the emerging threat. It can also create automated solutions for repetitive tasks related to threat management.

It is essential to note that AI tools can be used not only for information technology security prevention but also by cybercriminals to generate fake emails with fraud links or even to develop malware. Therefore, it is necessary to consider these risks as well.

Final Word

Artificial intelligence plays a crucial role in cybersecurity, primarily in the areas of prevention and assistance. However, we must acknowledge that AI is also becoming a tool for cybercriminals.

Nonetheless, future forecasts indicate even greater advancements in machine learning systems and deep neural networks, which will enable more effective prevention and combat against digital attacks.

Sources: IBM, TechTarget, SOPHOS

How AI is Applied in Customer Service

AI is increasingly being adopted in customer service as companies seek to enhance user experience and create more seamless interactions with their customers. There are several areas where machine learning can be applied.

First, generative AI can create content by analysing customer conversations and generating responses to their inquiries. Additionally, smart routing systems group incoming customer queries and direct them to the appropriate departments for more accurate responses.

Second, chatbots can be used to handle basic customer inquiries, offering quick responses at any time of day. They can also be deployed for tasks such as order tracking, product recommendations, or troubleshooting issues.

Third, natural language processing technology allows chatbots, voice assistants, and sentiment analysis tools to achieve more innovative and higher-quality results, as these systems are able to understand and accurately respond to more flexible queries.

Fourth, AI is particularly useful for analytics. By analysing customer feedback and other social interactions, AI systems can evaluate customer sentiment and identify areas within the company that require improvement.

Fifth, AI can analyse customers’ search and purchase histories, as well as their behavioural patterns, to generate personalized recommendations.

Finally, predictive AI can help improve business strategies by analysing customer behaviour patterns, enabling companies to anticipate their next steps or reactions in specific situations.

Opportunities and Challenges in Customer Service

One of the most significant advantages of AI in customer service is that customers can receive immediate answers to their queries at any time, 24/7. AI-driven analysis also allows companies to use real-time data to identify frequent issues and query types, helping to improve services or products.

Confidence in AI is further reflected in surveys. According to HubSpot, 72% of business leaders believe that AI can provide better customer service than humans, while 86% of AI-using leaders reported that these systems improved their ability to handle customer service situations at scale.

However, despite these positive trends, several challenges also emerge as AI becomes more prevalent in client support.

First, the lack of human interaction will become increasingly evident. Machine learning systems are not yet able to fully solve complex situations independently, and customers may miss the personal touch. It’s important to strike a balance and understand the audience’s needs.

Second, technical glitches and failures may occur, directly affecting customers and potentially leading to negative feedback and a decline in company’s reputation.

Final Word

The potential of AI in customer service seems limitless. These systems can help optimize and enhance various aspects of customer support, leading to promising results despite certain risks.

The future looks even more innovative, with voice generation technology allowing interactions with customers based on specific scenarios, and autonomous client support becoming more popular, where AI agents will be able to independently and effectively address customer queries.

Sources: Salesforce, sound of data, HubSpot

Areas Where AI Can Help in Parenting

AI-based parenting programs can be utilized in everyday tasks while raising children, whether finding solutions for situations that require explanations for decisions that might not seem favourable to the child at the moment or using digital tools to handle various daily activities.

Firstly, AI can be used for simple tasks, such as planning a weekly menu and creating a shopping list for necessary items. For large families, such tools can save a significant amount of time. Moreover, with specific input, such as children’s food preferences, these tools can generate personalized meal suggestions suitable for both adults and children.

Finally, based on the planned menu, AI can generate a detailed shopping list and organize it to ensure a smooth and efficient grocery shopping experience. Similarly, AI can be used to improve financial literacy and help create an effective budget.

Secondly, there is growing concern about the impact of screen time on young children and their developing dependence on technology. Parents often try to limit screen time, but this raises another challenge: finding alternative activities that are engaging and entertaining enough to make children forget about their devices. Here, AI can assist by generating activity suggestions based on available resources, such as toys, the nature of the games, and the child’s age group.

Thirdly, when faced with specific parenting challenges and not knowing how to handle or explain a situation properly, AI can create scenarios that help resolve the issue gently and without provoking additional negative emotions.

Specific Parenting Tools

One of the mentioned AI functions is the ability to suggest a detailed plan based on the described situation. An example of this is the Breda App, an AI-driven ChatGPT tool for parents that offers gentle parenting scenarios.

Another distinct tool is Nanni AI, which uses AI-driven translation algorithms capable of identifying different types of baby cries and determining the specific reason behind them. This startup focuses on enhancing overall well-being by improving sleep quality for both parents and their infants, offering tools to track sleep, feeding, and diaper changes.

The app, similar to Shazam, requires recording the baby’s cry, which it then categorizes into hunger, discomfort, emotions, or pain, and provides the most likely reason along with soothing suggestions. The company promises further service improvements, including the potential to detect certain crying anomalies in the future.

Final Word

While the use of digital tools, particularly AI in parenting, might seem unusual and even controversial – raising questions about parental competence and their ability to handle various situations creatively and manage time effectively – using such applications wisely and deliberately offers parents an innovative service that can significantly ease daily life. Sources: Breda, CNET, MOTHERLY

AI-Generated Voices Technology

Imagine a situation where you need to record your voice. It is likely that you won’t get it right the first time, and even in subsequent attempts, you may find things that make you doubt or want to start over, whether due to sound peculiarities or background noise disturbances.

Current AI capabilities can easily resolve these issues and simplify voice recording. AI voice generator tools can deliver impressive results, transforming written text into speech that sounds very realistic. Moreover, it offers a great opportunity and alternative for various business productions.

The main advantage of these apps is that they now feature highly natural voices, often indistinguishable from genuine ones. They also offer options to adjust the pronunciation, tone, pace, or even the emotional expression of the speech.

There is a significant demand for such apps, each catering to specific user needs and desires in different ways:

1. ElevenLabs stands out with its large voice library and an excellent filtering system. The library includes over 300 voices, featuring licensed AI-generated real voices, such as the sound of television actress Christy Carlson Romano.
2. Speechify focuses on human-like cadence. The app makes it quick and easy to achieve high-quality results with attributes such as consistency, appropriate pauses between words, speed, and more.
3. WellSaid allows users to adjust individual words or phrases to adapt their pronunciation characteristics, such as setting the pace or volume separately.
4. Respeecher offers the ability to include different vocalization and alter storytelling styles when inputting text. Users can also record their voices, which can then be used as templates for synthetic sound.
5. Altered focuses on a variety of storytelling styles. It also features an editor that allows users to adjust and adapt their own audio recordings.
6. Murf not only includes various voice adaptation features but also provides articulation control, allowing users to emphasize specific words more prominently.

Market Situation

The success of AI voice startup ElevenLabs demonstrates the rapid growth of the voice technology market and the importance of timely solutions. The company has achieved significant results within a few years, raising $101 million in investments. This rapid development is driven by new technologies – deep learning neural networks and generative AI.

The company offers several services. Firstly, Dubbing Studio—a service for dubbing any film, creating transcripts, and translations. Secondly, Voice Library, where users can sell their AI voice clones, and finally, the Mobile App Reader, which converts text and URLs into sound.

Another step forward is the NotebookLM feature, which allows users to listen to discussions about uploaded sources. Without incorporating personal information into model training, it helps users understand complex information from provided sources. The sources are discussed in a two-person dialogue format, not only reviewing them but also connecting themes and making summaries.

This feature is still experimental and will require continuous improvement. For now, it is only available in English, and the overview is based solely on uploaded sources. Nevertheless, it represents an innovative step into the future and provides an opportunity for those who learn and understand through listening.

The Challenges of AI-generated Voices tools

However, for now, such advanced solutions face significant challenges. The greatest threat is the misuse of these capabilities. AI voice cloning is sometimes used for less honourable purposes, becoming a tool for fraudsters.

Intellectual property and potential theft are also important concerns. Legal regulation, the initiation of necessary laws, and the introduction of licenses are essential to mitigate these risks.

Final Word

Despite the emerging challenges, this is a big technological leap and a new reality in everyday life. Although there is still a lot to be done to make these AI generated voices tools even better, we can already see how such solutions offer versatile possibilities and adapt to the user.

Sources: TechTarget, Google, Zapier

AI’s Potential to Replace Literary Critics

A literary critic is not just any reader. These are individuals with specific knowledge and abilities to apply literary theories, models, and other concepts to academically assess the quality, originality, and societal impact of a literary work.

To critically evaluate a work, textual analysis is essential. Some of the key elements involve understanding the writer’s style, tone, and the themes they explore from various perspectives, as well as grasping the subtleties of the plot and the characteristics of its characters. All of this contributes to a quality assessment of the work.

The question arises: how capable is AI in this area? Essentially, this technology has vast databases and the potential to be programmed to include all the necessary aspects in its analysis.

When properly trained, machine learning can be invaluable, as it has the ability to process large amounts of information quickly, saving time. It can also recognize certain literary models or methods and detect their recurrence across different texts.

Moreover, this partially reduces the issue of objectivity, as a literary work can be evaluated impartially. Additionally, natural language processing capabilities allow it to analyse texts beyond the surface, as it can understand context and offer insights that may go unnoticed by human readers.

Challenges of AI as a Literary Critic

Despite AI’s potential in this field, several challenges arise. First and foremost, artificial intelligence is essentially programmed to operate according to specific rules. However, literary criticism and analysis are fundamentally interpretive. Therefore, there is a risk that system might approach a text from a particular angle, potentially missing other important details.

Complex literary works often involve a lot of contextual material, such as history, specific to a location or time period, or information linked to particular knowledge, which system might not recognize unless it is explicitly provided.

These aspects become the primary challenges for neural network in performing literary analysis, as it risks becoming limited and incomplete.

Final Word

At least for now, it seems that after considering all the possibilities and risks, the best solution is the collaborative partnership between humans and AI, where machine learning is not left to perform literary analysis independently, and human critics contribute their insights and observations.

As machine learning continues to advance, there is a growing possibility and threat to current literary critics that machine tools might perform their work faster and with the same level of quality in the future. Sources: Medium, Kharis Publishing, Powerdrill

The Significance of Automated Solutions for Human Intelligence

Today, data search and retrieval have become highly advanced. Technologies such as GPS navigation, voice assistants like Alexa, and our calendars perform specific tasks for us, sending reminders about important upcoming events.

On one hand, artificial intelligence brings a certain convenience, but it also limits self-reliance. For instance, constant use of GPS navigation diminishes a person’s ability to orient themselves independently and fosters a dependency on the technology.

We now hand over our critical thinking and skill development to algorithms and search engines, which perform tasks for us, sometimes without us realizing that this essentially makes us less productive. While these solutions significantly ease our lives and are often very convenient, it’s crucial to find a balance and understand that such solutions don’t always bring purely positive outcomes.

Artificial intelligence dulls our thinking abilities because many people trust it and delegate various tasks to it. Also, with the help of algorithms, we receive personalized content or suggestions in many areas, which we often choose without critical evaluation. This also encourages dependence on various smart technologies and automated solutions, as we become lazier, knowing that many tasks can be accomplished with just the press of a button.

Although AI-based technologies save time, they also negatively impact decision-making processes. AI gradually limits, or in other words, suppresses, human cognitive skills like intuitive analysis, critical thinking, and creativity, which should be employed when addressing challenging situations. People have simply grown accustomed to receiving solutions quickly, with little personal effort, thanks to smart technologies.

Technological advancement has inevitably confined us to the digital space and significantly reduced real, face-to-face interactions. This has also led to a decline in social skills and emotional expression.

The important question remains: how do we properly use artificial intelligence? Should we fully rely on it, allowing it to make decisions on our behalf, or use it as a tool to assist us in creating creative solutions to problems?

Knowing these emerging challenges, each of us should look for the best solution for it and find a balance between all these things.

Final Word

In the digital age, amidst all the functionalities and conveniences provided by smart technologies, it’s essential to maintain a balance and critically assess how we use digital tools in our everyday activities.

Technologies developed by artificial intelligence should be used consciously and critically evaluating their impact on personal development in the discussed areas and be a kind of auxiliary tool.

Sources: Inc, USC Dornsife, Nature