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10 Generative AI Myths You Need to Stop Believing Now

Original source : 10 Generative AI Myths You Need to Stop Believing Now

Many people are already familiar with the concept of generative AI, yet, there are still numerous myths and misconceptions connected with it. However, being aware of the reality that lies behind such opportunities is indeed essential to work with all these features in appropriate ways.

Here, ten myths regarding generative AI are exposed to assist people dealing with reality and fake information.

1. AI Can Do Everything Humans Can Do (And Better)

Without a doubt, the most common myth around AI is that it can replicate all the activities that people can and even exceeds their capability levels. Despite appreciable advances in forms of applications embracing generative AI that includes language and vision, and even artistic products, an AI system is a tool developed by man. Artificial intelligence is not as holistic as human intelligence, it does not have personal insight, emotions, and self-awareness.

AI used effectively for tasks that are clearly defined. For example, it can process large chunks of information in a short span of time than it would take any person, thus helpful in areas like data analysis and forecasting. But it is weak at solving problems that involve practical reasoning, moral reasoning, or understanding of contingencies. Generative AI can create text, images from the learned patterns from the provided data but it does not comprehend the content as a human does.

2. AI Writing is Automatically Plagiarism-Free

Another myth is that AI writing does not have plagiarism since what the system produces is original. However, as we have seen, generative AI works on the availability of current raw data to generate content, it cannot create new text. It implies that one is never certain that AI is not regurgitating fragments of the data set input to it, meaning questions relating to originality and plagiarism could arise.

AI in content generation, thus, needs to have well-developed checks on originality to ensure the content produced is original and not plagiarized. There is always some use for programs such as plagiarism detectors, but they should always be reviewed by a person. For the same reason, the training data needs to be selected with equal attention in order to avoid reproducing someone else’s efforts. It is important to understand such limitations to achieve a reasonable level of AI application in content creation.

3. AI Completely Replaces Human Creativity

Another myth is that AI affords to take over creativity by humans. Thus, AI can support and improve creative tasks, but it will never possess the creativity that is inherent in human beings. Creativity goes beyond ideas of placing together of different ideas to form new compositions; the same encompasses emotional aspects, cultural aspects and the aspects of innovation that center on the experiences of human beings.

Referring to music, art or written text, generative AI is as creative as a parrot, in the sense that it will recreate creativity that has been passed through it by using patterns which have been fed into it. It doesn’t come with the purpose of creating. On the contrary, AI can be perceived as a tool that can supplement human imagination by giving more ideas, more time, and the means for the idea manipulation.

4. AI is Unbiased and Objective

One more myth is that of AI being completely neutral and free from an opinion and prejudice. Actually, any AI system captures the existing biases and discrimination in the data used for training and the algorithms employed in a system’s design. By definition, an AI system is as good or as bad as the data that is given to it as input; therefore, if the data fed into an AI system is prejudiced, the outcome will also be prejudiced. This is a problem especially on profiles that require sensitive decision making such as hiring, police force, lending among others.

It is important to select training data that is diverse and inclusive, perform bias checks on AI regularly, and incorporate fairness constraints in AI algorithms. These issues have to be dealt with and addressed so that through transparency and accountability in the development and deployment of AI, AI systems used are fair and equitable.

5. AI will Take All Our Jobs

One of the main issues is the idea that AI will take our jobs. To some extent it is true that through the introduction of innovative technologies such as AI and automation they spark threats of job loss; however, it is equally important to note that they are more of a job reinvention process. In the human-robot interaction, AI is useful as it can perform routine and uninteresting activities that do not require human creativity.

In the past, people highlighted the fact that generation of technology leads to emergence of new employment forms while leaving some of the existing positions without demand. The major challenge therefore lies in how the workers are going to undergo a transformation by developing new skills that are inline with AI. Continued and expanded access to education and training that relates to the emerging areas of digital literacy, AI, and data science will have to be ensured in the near future.

6. AI is a Silver Bullet for All Your Content Needs

Some think that with the help of AI one can face no difficulties and overcome any hurdles in content creation. AI can truly improve the content generation process but that does not mean it is the universal solutions. Many things which an AI creates are to be reviewed by a human being in order to avoid mistakes, update and improve the quality. Also, AI is unable to grasp context and subtlety, which are critical for producing quality and valuable content.

AI also has an ability to write first drafts, provide suggestions and even promote content with help of SEO. But further adjustment and enhancement in the content can only be done by human inputs so as to meet the exact standard and effectively appeal to the audience.

7. AI Can Fully Understand and Replicate Human Emotions

Among them let me mention another one — AI can capture and mimic human feelings. Thus it is seen that though there can be an analysis of emotional signals and a response that appears sympathetic, there is no feeling. AI can be designed to identify signs of emotions in people’s actions and words, but it does not mean that it really knows or can feel emotions.

Affective Computing or the Emotional AI is the branch of artificial intelligence that is focused on making human-computer interactions dependent on the emotions. However, these systems work on predefined rules and defined data pattern, which gives them no emotional intelligence like that in the human heart. It means that AI can only imitate the emotions but cannot replace the feeling that people in the same mood can share.

8. AI is Completely Secure and Trustworthy

Believing that AI is fully safe and trustworthy is a misconception that one should better avoid. There are several security risks associated with integrated AI systems, such as attacks, hacking, and misuse. The issue of security is fundamental while deploying the AI system to ensure that the system is protected both from an external and internal attack.

AI developers and users should have appropriate security measures like encryption, auditing, and monitoring that should be put in place all the time. Further, there is a need for ethical standards and legal frameworks on the use of AI to encourage its utilization in a proper, accountable manner. It is worth remembering that trust can only be gradually established through constant engagement in addressing security and ethics issues.

9. AI is Infallible and Always Accurate

The other myth is that the AI is always perfect and does not make any mistakes. Thus, it might be asserted that despite of the high level of accuracy AI could produce a great number of mistakes. AI systems can also error, for instance, because of the lack of a sufficient amount of training examples, existence of some algorithm defects, or unpredictable events. There are problems when relying on the results of AI without people’s intervention or monitoring.

But it is important to understand that AI is a tool that can strengthen human capacities, not remove them. AI solutions require human experience and decisions for the validation of the application outputs for accuracy and reliability. The awareness of AI’s drawbacks is useful for decision-making about AI’s best application.

10. AI is Only for Tech-Savvy Experts

The last myth is that only people with high IT skills can implement AI. However, creating and implementing the sophisticated AI systems necessitates a certain level of technical expertise; yet, some of the AI tools and applications are built to suit everyone’s needs. AI technologies can be introduced and implemented by a wider audience because of friendly interfaces, ready-made models, and documentation that can be easily read by Non-IT specialists.

Business entities and other users do not need a strong technical background when interacting with AI technologies and rather use various AI platforms and automated machine learning tools, as well as applications. These tools bring artificial intelligence to the minds of more people so that a wider circle of individuals can try using AI for different tasks.

Conclusion: Separating Generative AI Fact from Fiction

Generative AI is one of the most influential technologies today, yet, it is important to cut through myth and hype with the possibilities. It shows information about myths and facts about AI aiming to provide the people with reasonable expectations and actually try to put its abilities to use in a proper and safe way. However, understanding AI’s capabilities and drawbacks is the key to using this powerful invention to help enhance human creativity, reduce costs and optimize the way to develop new products and services while contemplating AI’s ethical and security issues.

If you want to read the full blog then click here: 10 Generative AI Myths You Need to Stop Believing Now

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backtothefuturefan88 · 11 months ago

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I’m back with an another redesign of Ahsoka Tano; this time it’s her second padawan outfit (season 3-5).

I drew her markings on her face and Lekku (which I did make longer) to match a little more to how she looks in Rebels; I didn’t like how different she looked in Rebels originally, but the design has kinda grown on me.

I kept her Akul teeth, purple sash that hangs from her belt, and black eyes from Shaak Ti’s original concept design, but changed her jewelry slightly from my first design.

I wanted to give her robes that were more similar to traditional Jedi robes compared to her original outfit, but changed to the sleeves to be a cut open design and her skirt splits at the sides to allow more movement.

The piece that hangs from her belt is from concept art for Shaak Ti.

Her belt is based off of Obi-Wan’s with two lightsaber clips next to each other, but I added her original yellow belt clip, and a pack in the back that Fives has when he becomes a Arc Trooper; I also added a chain with Anooba teeth that hangs from the belt that she kept as trophy for surviving the Citadel.

The last thing I added was the Clone Armor. The chest piece has the Jedi symbol on her right hand side, and a pattern of the holes in her armbands from her original outfit.

The boots have the diamond pattern her leggings have from her original outfit.

And lastly I added different aurebesh names across her armor; I encourage you to translate them.

I’m really happy with design! I think I like it more than my first one.

What do you think of this one?

And should I redesign Ahsoka’s other outfits?

I probably will, but what do you guys think?

(Part 3 👇)

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