Ambika Bhandari

Premium reporting on technology, startups, VC funding, and software from Techfastly tagged with AI. Read about themes, trends and strategies for AI.

Artificial Intelligence

Is Artificial Intelligence a Threat to Journalists and Writers?

Artificial Intelligence (AI) has gone through several developments over the years. Various industries around the world are taking the help of AI to get things done faster and better! News Industry is one such industry that has taken baby steps towards using Artificial Intelligence in their newsroom. For example, <a href="https://blogs.thomsonreuters.com/answerson/making-reuters-news-tracer/">the News Tracer at Reuters can scan through Twitter to find out breaking news</a>. Similarly, many researchers are developing algorithms that can discriminate between true and false information. <h3 id="the-fake-news-or-false-information-issue">The ?Fake News? or False Information Issue</h3>The term 'Fake News' is popular in the Internet world. However, the correct word to describe unauthentic news is "False information"! Fake news is associated with political agendas. But anyway, both of these are a threat to the netizens. False news getting viral can have an impact on society. It creates a wrong notion. Once spread, it is impossible to contain. Although, with time, people are developing skills to detect false information. But most of the netizens aren't tech-savvy. So, they become the victim of fake news. The best way to reduce such viral news is to filter them out before they spread. This is where AI comes in handy. AI algorithms use spam filtering technology for filtering fake news. The researchers are developing a mechanism that can differentiate between human and machine-generated content. <h3 id="grover-the-fake-news-detector">Grover: The Fake News Detector</h3><a href="https://thenewstack.io/grover-ai-detects-machine-generated-neural-fake-news-by-also-generating-it/">At present, the most reliable AI algorithm to fight against fake news generators is Grover</a>. Its goal is to detect any "neural fake news" that is doing rounds on the internet. The Grover can not only detect but also generate fake news. The generator mechanism follows the same habits and traits as other fake news generators. Therefore, it identifies any AI fake news. However, the main concern is that the fake news generators replicate the exact style of human writing. With time, they are only getting better at generating humane copies. Therefore, even for an AI like Grover, it is difficult to discriminate between machine-generated and human drafted articles. <h3 id="the-mechanism-behind-fake-news-detection">The Mechanism Behind Fake News Detection</h3>AI uses a similar technique that we employ to discriminate and judge false information. The algorithm compares two similar write-ups. It goes through the facts and matches it with a reliable source. The reliable source is the one that contains the facts and information. So, Al uses virtual data libraries to learn all about human writing styles. RealNews, Kaggle, and George McIntire are some of the datasets used for the <a href="https://arxiv.org/ftp/arxiv/papers/1810/1810.07829.pdf">Grover algorithm</a>. We also look at the headline, description, and feature image to identify whether a link is clickbait. The AI algorithm uses the same process to identify fake news. However, the new algorithm, <a href="https://qiskit.org/textbook/ch-algorithms/grover.html">Grover, can detect only 92% of false information</a>. The Grover algorithm can search any unique content, in this case, 'non-human' content. There are many websites like <a href="https://notrealnews.net/">NotRealNews.net</a> that use Artificial Intelligence to generate fake news stories. These fake news stories resemble the original stories. To detect fake news and false information Artificial Intelligence algorithm learns how to write them first. However,<a href="https://techcrunch.com/2019/02/17/openai-text-generator-dangerous/"> OpenAI has announced that its AI writer is too dangerous to publish articles publicly</a>. The 'Grover' creators, on the other hand, feel that it is safe for the AI to learn to write fake news first. In <a href="https://techcrunch.com/2019/06/10/to-detect-fake-news-this-ai-first-learned-to-write-it/?guccounter=1&amp;guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&amp;guce_referrer_sig=AQAAAFCsJ2fFyiXU-thFwFgwelbhICfc-Hz0dXAakiPAwH97Fl6hI24-SpLVl9UviIQuoEYiPE8-R6LrHT-e9NwbEu">an article on Techcrunch.com</a>, <a href="https://rowanzellers.com/grover/">Rowan Zellers, the Grover team lead</a>, said, "These models are not capable, we think right now, of inflicting serious harm. Maybe in a few years, they will be, but not yet. I don't think it's too dangerous to release ? really, we need to release it, specifically to researchers who are studying this problem, so we can build better defenses. We need all these communities, security, machine learning, natural language processing, to talk to each other ? we can't just hide the model, or delete it and pretend it never happened."Grover and the other Artificial Intelligence algorithms are becoming efficient by generating more fake news articles and then identifying them. If the generated articles are not believable, they keep developing content that can replicate the human writing styles. In this way, they learn how to detect fake news. <h3 id="deepfakes-and-artificial-intelligence">Deepfakes and Artificial Intelligence</h3>Another issue we are facing is the "Deepfakes"! <a href="https://www.scientificamerican.com/article/detecting-deepfakes1/">Deepfakes are fake photos and videos created by AI. The AI uses several pictures of a real object and superimposes them to create a similar fake image</a>. In this way, it also generates images of fake people. However, when a person watches such videos or pictures, he or she easily believes them. <a href="https://www.theguardian.com/technology/ng-interactive/2019/jun/22/the-rise-of-the-deepfake-and-the-threat-to-democracy">The Deepfakes are being used for Propaganda these days</a>. Doctored images and videos are often employed to create unrest. They are even used to tarnish the reputation of celebrities. It is not easy to fight against deepfake content. However, researchers are trying to develop algorithms that can identify fake videos and pictures. <h3 id="how-can-you-help-to-fight-against-fake-news">How Can You Help to Fight Against Fake News?</h3>Fake news doesn't get viral on its own. While we surf the internet, we share a lot of these fake news stories knowingly or unknowingly. <a href="https://www.statista.com/statistics/657111/fake-news-sharing-online/">According to a survey</a>, 10% of the participants shared fake news knowingly. 49% of them shared content that they later learned that the news was fake. So, the only solution for us is to learn to identify fake news. If we do not understand whether a particular news is true or false, we should avoid sharing it! It may take time to judge whether the content is authentic or not, but it's worth the time. So, the next time you find an interesting article, check a few more similar news stories. This would help identify fake news.<h3 id="are-there-other-artificial-intelligence-tools-to-fight-fake-news">Are There Other Artificial Intelligence Tools to Fight Fake News?</h3>The Grover algorithm isn?t the only AI tool working against fake news. There are other tools as well. Some of them are <a href="http://hipporeads.com/tool-called-hoaxy-fact-checks-fake-news/">Hoaxy</a>, <a href="https://www.snopes.com/">Snopes</a>, and more. Hoaxy is a tool that identifies fake news websites. On the other hand, Snopes is a website that detects fake news stories on the internet. However, these are not as efficient as Grover. Dealing with Fake News is constant trouble for the world. With Artificial Intelligence and Big Data, we are getting stronger in our combat against the fake news generators on the world wide web. However, we are only at the surface. Artificial Intelligence tools can not only identify fake news but also replace them with the correct facts. <a href="https://www.hindawi.com/journals/complexity/2020/8885861/">The researchers are working on algorithms that can reduce the fake news menace</a>. We will have to wait and see how things unfold in the future.

Can Artificial Intelligence Detect Fake News?

How Does OpenAI's GPT 3 Work?

If you own a smart device, you must know about Google Maps. It is our 'Go to' app for searching destinations and directions.According to <a href="https://blog.google/products/maps/google-maps-101-how-ai-helps-predict-traffic-and-determine-routes/">Google's blog</a>, people drive over 1 billion kilometers in over 220 countries every day. And they do it with Google Maps.Google Maps are known for its accurate traffic predictions and expected time of arrival (ETA). Ever thought, how is that happening? Well, it is the magic of DeepMind's AI tool.It uses machine learning tools to study how much time it takes for a person to arrive at a destination. Then it stores the data to show it to a different person wishing to visit the same place.Along with that, it uses an algorithm to predict the ETA and live traffic on a particular route. With DeepMind?s AI model, Google Maps made sure we get only the accurate data!<h3 id="what-is-deepmind-ai-lab">What is DeepMind AI Lab?</h3>DeepMind is an Alphabet research AI lab. Its research team tests and studies various AI programs. If you check their<a href="https://deepmind.com/blog"> blog</a>, you will find works on AI games, health, and more.It makes one wonder how many things can Artificial Intelligence do!The team of engineers, scientists, AI experts, and more believe that Artificial Intelligence could be humanity's most useful invention. So, they study various things that can make people's life easier.Last year, Google got DeepMind onboard on Google Map project. The main goal was to make Google Map prediction top-notch and provide better service to users.<h3 id="how-does-google-map-predict-live-traffic">How does Google Map Predict Live Traffic?</h3>For traffic prediction, the AI collects data from various sources and feeds them to the algorithm. It thus stores the data and learns how to use it to predict the traffic flows.It collects several data from our phones such as live location, past traffic memory, construction sites location, road size and more.Additionally, it uses public information to find the location of road damage, size, and direction, road quality, and more.For example, the AI algorithm predicts the chances of traffic jams if there is an accident. It receives data of any damaged road from the local Government. Then uses it to predict the traffic around it.It collects all these data from various sources and feeds them into DeepMind's neural networks. The AI studies and predicts the traffic. However, during the COVID-19 lockdown, there was a change in the traffic pattern.The scientists added new data into the neural networks to predict traffic during lockdown periods.Google Maps product manager <a href="https://blog.google/products/maps/google-maps-101-how-ai-helps-predict-traffic-and-determine-routes/">Johann Lau said</a>, ?We saw up to a 50 percent decrease in worldwide traffic when lockdowns started in early 2020. To account for this sudden change, we've recently updated our models to become more agile ? automatically prioritizing historical traffic patterns from the last two to four weeks and deprioritizing patterns from any time before that.?The AI algorithm divides the maps into several segments. They are called "Supersegments".There is no distinct size of these supersegments. However, they change with the traffic. One segment collects about terabytes of data.So, you may assume the size!The supersegment is a group of adjacent streets that have the same traffic volume. Each group has its neural network which does traffic prediction.It uses a specific kind of neural network called ?Graph Neural Network?. Google considers this as the most suitable AI algorithm for traffic prediction.<h3 id="how-deepmind-s-ai-help-in-eta-prediction">How DeepMind?s AI Help in ETA Prediction?</h3>Before partnering with DeepMind, Google already had a 97% accuracy rate of the expected arrival time for a destination.For ETA predictions, DeepMind uses the Graph Neural Networks. The <a href="https://deepmind.com/blog/article/traffic-prediction-with-advanced-graph-neural-networks">accuracy rate of the expected arrival time was up by 50% </a> in major cities around the world.Using the traffic data from various segments (as mentioned above), it collects current traffic information. It won't be able to show future traffic like condition of traffic after 20-50 minutes.For showing future traffic conditions, it uses historical data from various sources. The AI algorithm combines the current traffic and the historical data to predict ETA to a destination.<figure class="kg-card kg-image-card kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/71b2d763c59b825a5498db5441d3d0b4.jpg" class="kg-image" alt loading="lazy" width="684" height="403" srcset="https://techfastly.com/content/images/size/w600/2021/04/fsdfdsf.jpg 600w, https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/71b2d763c59b825a5498db5441d3d0b4.jpg 684w"><figcaption>Image via <a href="https://deepmind.com/blog/article/traffic-prediction-with-advanced-graph-neural-networks">DeepMind Blog</a></figcaption></figure>For example, the algorithm has data of the rush hour of a route in Sydney for a random Monday. But it turns out that a Monday is a holiday but it will show it is a rush hour for future predictions. So, it will also show that the ETA is much longer than the reality.However, the current traffic and the ETA will be accurate on-road, thanks to the Graph Neural Network. Moreover, data on road quality, accidents, and more are added to the model to raise the accuracy rates for ETA and traffic prediction.<h3 id="how-does-it-work-for-you">How Does It Work For You?</h3>Let's say you are heading towards the airport. When you leave your house, the traffic shown in Google Maps is normal and free-flowing. There is no indication of any disruption or bad roads.However, as you are on the move, Google Maps will start predicting live traffic details. It will tell you the exact condition of traffic as you move through the routes.So, 5 minutes into the drive, it predicts that you may get stuck in a traffic jam. It also tells how much time it might take to get out of it. Therefore, it starts suggesting routes that can help you reach the airport on time.Thus it will help you avoid the traffic and also reach on time.<h3 id="ready-to-try-out-the-new-features">Ready To Try Out The New Features?</h3>Google Maps partnering with DeepMind's AI lab has brought a revolutionary change in the application. It made the predictions 50% more accurate. Now anyone can learn about traffic jams and ETA without relying on Radio FM or assumption.The Graph Neural Network delivers accurate data for the user. Moreover, it will also suggest roadways that can lessen the travel duration. So, don't forget to use Google Maps the next time you are on the road.

Premium reporting on technology, startups, VC funding, and software from Techfastly tagged with algorithm techniques. Read more about algorithm techniques.

Algorithm Techniques

DeepMind?s AI: How it Predicts Google Map?s ETA?

Artificial Intelligence (AI) has been bringing massive transformations in various industries in recent years. We see AI impacting different parts of life and making possible things that were once fantasy.Although there is a fear that AI will take away our jobs, it is not so. On the other hand, AI will help us progress in different sectors. According to<a href="https://www.forbes.com/sites/amitchowdhry/2018/09/18/artificial-intelligence-to-create-58-million-new-jobs-by-2022-says-report/?sh=1f4a69044d4b"> Forbes</a>, by 2022, AI will create 58 million jobs.So, we should try to welcome these changes and make life easier.&nbsp;Another sector where Artificial Intelligence is bringing revolution is the UX (User experience). In this article, you will get an idea of how AI helps in improving UX for businesses.<h1 id="what-is-ux-and-why-is-it-important">What is UX, and Why is it Important?</h1>User Experience (UX) is how one user feels when he or she interacts with any system. It can be a website, mobile application, device or software.Most businesses are shifting their focus to creating a better customer experience. Almost all successful companies are known for an exceptional understanding of the audience's interests and needs. To satisfy customer requirements, it is essential to have an understanding of their likes and dislikes.Therefore, companies try to collect data on customer requirements and experience to create the right products and services. The product or service must make a good first impression. According to<a href="https://www.forrester.com/report/The+Six+Steps+For+Justifying+Better+UX/-/E-RES117708"> Forrester Research</a>, a good UX design on a website can boost conversion up to 400 percent.So, most companies are also going for a proper UX design for their websites and services.&nbsp;UX is important because it helps create a positive experience for potential customers. When they have a positive experience, they remain loyal to the brand for many years. All these years, this job fell in the hand of the marketing research teams.However, in recent years, many companies have been bringing in AI and machine learning technologies to create a better user experience for their customers.<h1 id="how-ai-improves-ux">How AI Improves UX?</h1>If you study the goals of AI and UX closely, you'll find that they are similar. They are designed to study human behaviour and interpret it. With the interpretation, they find out what is the next thing the customer might do.In this way, predictive analysis is done, which is utilized by companies to map out their plans properly.&nbsp;But how exactly can AI help UX? Let's take a look at a few ways.<h2 id="intelligent-algorithms">Intelligent Algorithms</h2>AI works on algorithms. With the help of these algorithms, AI can collect information about website visitors or application users. Then it uses these data to optimize the system for future use. It keeps on learning and adjusting the data about the user experience.&nbsp;The ultimate goal is to provide users a personalized and engaging experience.<h2 id="deep-learning">Deep Learning</h2>AI uses a process that we know as deep learning. With this mechanism, it can analyze thousands of different variations and generate alternatives. This information can be used in UX for adding buttons or graphics on a website or an app.For example, with AI, we learn at what places a user clicks the most on a website. We can enhance those areas with striking graphics or a button. As most users are clicking on certain regions, AI can understand others will do the same.With this information, UX can be enhanced by changing the website's design by adding a few things here and there. Deep learning technologies help us get behavioural data which helps AI to improve the UX of any system.<a href="https://www.hotjar.com/heatmap-analytics/">Hotjar</a> is a popular AI tool that helps you learn where exactly people are clicking on the website. In this way, one can easily find the spots to enhance.<figure class="kg-card kg-image-card kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/08a3f4e1de811fad195192353c4cc605.jpg" class="kg-image" alt="" loading="lazy" width="1139" height="733" srcset="https://techfastly.com/content/images/size/w600/2021/04/drgrt.jpg 600w, https://techfastly.com/content/images/size/w1000/2021/04/drgrt.jpg 1000w, https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/08a3f4e1de811fad195192353c4cc605.jpg 1139w" sizes="(min-width: 720px) 720px"><figcaption>Image via <a href="https://www.hotjar.com/heatmap-analytics/">Hotjar</a></figcaption></figure><h2 id="testing-using-ai">Testing using AI</h2>UX professionals need to study various metrics to improve the whole user experience of any product or service. AI can help with this! It has the right tools that help in evaluating and track the UX metrics, such as:<ul><li>Location of users</li><li>Bounce rates</li><li>User Flow</li><li>Categories or Product reviews</li><li>Session times</li><li>Pages view</li><li>and more.</li></ul>With the help of these metrics, the UX professional will understand how they can improve the user experience. <a href="https://analytics.google.com/analytics/web/provision/#/provision">Google Analytics</a> is one such product that uses AI to provide these insights into a website.For example, a UX professional learns that most website visitors are clicking on an image of a product. So, it would be better to enhance that picture or bring it to the front page. In this way, the users don't have to go through the pages to get the product.<h2 id="no-biases-in-testing">No Biases in Testing</h2>When you use AI for UX, there are no chances of any biases. AI only shows the reality of what users want or do with the product or service. So, there is no need for A/B testing or split testing.In A/B testing, personal reasoning can impact the result. Say there is an A/B test with a result showing that sample A has received more attention. However, the professional may still want to go for B as they may think that users will like it more.A/B testing is not transparent. The professional is unable to see what are the reasons a person chose a particular sample. However, when you use AI for such metric testing, there are no biases.AI will show only the reality. It will give data on what people like and also show information about why they do so. As AI relies on hard data, you will likely get a clear picture of what the users want.In this way, UX professionals will deal with unbiased data when working with AI.<h1 id="ways-companies-can-improve-ux-with-ai-">Ways Companies can improve UX with AI:</h1>AI can help UX professionals to understand the importance of unbiased user data. This user data is the key to creating a positive experience for the customers.Here are the five ways AI can help improve UX:<h2 id="1-emotion-ai">1. Emotion AI</h2>Do you know AI can detect emotions as well? The mechanism is called Emotion AI or affective computing. Gadgets with emotional intelligence can understand the emotional channels of communication as well.It helps the AI learn and interpret verbal and non-verbal human communication. For example, when a person smiles, the AI can tell whether it's a happy or sad smile.<figure class="kg-card kg-image-card kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/476c6721d16b8ba139b491350d99c6f1.jpg" class="kg-image" alt="" loading="lazy" width="1400" height="535" srcset="https://techfastly.com/content/images/size/w600/2021/04/HeaderV8-5.jpg 600w, https://techfastly.com/content/images/size/w1000/2021/04/HeaderV8-5.jpg 1000w, https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/476c6721d16b8ba139b491350d99c6f1.jpg 1400w" sizes="(min-width: 720px) 720px"><figcaption>Image via <a href="https://blog.affectiva.com/announcing-inaugural-emotion-ai-summit-event-at-mit-media-lab">Affectiva</a></figcaption></figure>This technology includes:<ul><li>Machine learning algorithm</li><li>Facial recognition algorithm</li><li>Data analysis</li></ul>UX professionals can learn about the emotional responses to a company's products, content, website or services with emotion AI. The technology can be easily used on the footage of CCTV recordings in stores to understand people's emotions while looking at different products of a particular brand.If the businesses learn the people's reactions to their brand elements, they can take the UX professionals' help to make necessary changes. For example, it can change the brand's logo or the content that goes on the website.With enhanced content on the website, the company can expect better engagement. In this way, emotional AI can help optimize different elements of a company.One good example of emotion AI in action is<a href="https://xconomy.com/boston/2018/03/21/affectiva-launches-a-i-tech-to-help-cars-sense-your-emotions/"> Affectiva's emotional car software</a>. It can detect when a driver is angry or unfocused while driving. The AI installed in the system will then take control of the car and prevent any accidents.<h2 id="2-complex-data-analysis">2. Complex Data Analysis</h2>Even these days, UX professionals depend on heat maps and A/B testing to learn all about user engagement. However, AI can easily provide more in-depth information regarding the user experience.UX teams can use AI deep learning mechanisms to analyze and track huge data sets. AI guarantees accurate behavioural data, which is not possible through traditional methods. Many businesses are making use of behavioural data in their UX processes.For example, Joseph Turner, a shirt retailer, took the help of <a href="https://www.segmentify.com/success-stories/joseph-turner-success-story">Segmentify's AI solutions</a> to expand their business. With AI support, they could easily understand what users liked and disliked. They made 2.6 times higher conversions with the help of AI solutions.With the AI-produced data, they could analyze which places to optimize on their website. And this resulted in 20% more items in the basket.<h2 id="3-personalized-advertising">3. Personalized Advertising</h2>Although people think UX professionals only have to deal with the website or the landing page. However, the truth is these professionals start working from the first moment a product or a service is introduced to the public.The struggle to get better engagement starts from the first introduction, which is from advertising. Advertising helps grab the attention of users online to a certain product. When intense competition exists in the market, it is essential to make better ads.Now a person has thousands of brands to choose from. The trick is to become a superstar in front of that person so he or she goes for your product. Moreover, with only an <a href="https://www.medicaldaily.com/human-attention-span-shortens-8-seconds-due-digital-technology-3-ways-stay-focused-333474">eight-second </a>attention span to impress, the job is more difficult than before.AI can help UX designers come up with more personalized and creative ads for customers. As most of the leads are now available online, social media ads are more common.<figure class="kg-card kg-image-card kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/a30657182f079a9c52640dd547842681.png" class="kg-image" alt="" loading="lazy" width="595" height="221"><figcaption>Image via <a href="https://automat.ai/resources/personalized-marketing-everything-you-need-to-know/">Automate Technologies</a></figcaption></figure>AI produces more in-depth data on the users when they interact with the brand's social media pages. So, every time a user likes a page, comments on posts or displays any interest in any product, the AI will collect the data.Then it will interpret the data to segregate the audiences into distinct groups with certain attributes. The UX designer can then look at this information to design the ads accordingly.For example, the AI data shows that most of the users showing interest in the brand and its other product ads are between the ages of 16-20. So, when the next ad is planned, it should be optimized for this age group.&nbsp;In this way, the ad will gain better attention from this age group.<h2 id="4-chatbots">4. Chatbots</h2>Chatbots are the most popular ways in which AI can improve the user experience of the brand. These are virtual assistants who talk to the user when there is no real customer support.Using natural language processing, chatbots can speak just like human beings. In this way, they help businesses double their customer service metrics.According to<a href="https://www.capgemini.com/2018/02/can-a-cpg-company-use-ai-to-directly-influence-a-consumers-purchase/"> Capgemini</a>, 75% of the businesses that have used chatbots have reported a 10% increase in customer satisfaction.Moreover, chatbots can work 24/7, unlike their human counterpart. So, it can also handle unruly customers who take out their frustration on customer care service professionals. However, if you fear chatbots will take over customer care professionals' jobs, you are wrong.No matter what, during any conversation with the bot, the human professional will have to take over. It helps in maintaining the human touch the users want from any company. Therefore, in the sector of customer service as well, AI can help UX professionals very well.<h2 id="5-automation">5. Automation</h2>UX testing can use automation during the research process to make work faster. AI automation can detect the problems that users experience during interacting with any product, service or website.With the correct automation tool, the company can reach out to the user who has a problem with anything related to the company. The AI collects the data and presents it to the company. In this way, the UX professional can use the data to prepare a better system for future users.Automation in UX testing can help in resource-saving, cost-reducing, performance testing and more.Amazon is one of the best examples of using automation in UX. It has gained<a href="https://www.forbes.com/sites/blakemorgan/2018/07/16/how-amazon-has-re-organized-around-artificial-intelligence-and-machine-learning/?sh=511f43d47361"> a 35%</a> increase in its revenue with the help of personalized recommendations. You must have come across these recommendations when using the Amazon shopping website.<figure class="kg-card kg-image-card"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/4a3be1d72fa8bdf21fc839749c2815bf.png" class="kg-image" alt="" loading="lazy" width="488" height="198"></figure>The AI here records all the data about you, including your past buys, age and location, to provide personalized product recommendations.<h1 id="conclusion">Conclusion</h1>Artificial Intelligence is still evolving. Now it has limited assistance for UX professionals. Although, whatever assistance AI provides is helping businesses grow rampantly.Almost all the top business giants are using AI's help to get their things going. It helps in saving money and also makes the work more efficient. However, no company can grow without giving a better user experience. So, recently most companies have been using AI to enhance customer experience.From chatbots to personalized recommendations, we see a lot in all the UX elements. AI is also helping UX professionals develop better user-friendly designs for websites and applications.

5 Ways Companies Improve UX with AI

AI algorithms can flag the content even before 10 views are completed. Although, are algorithms really the solution to filter the content on social media platforms? 

How AI Filters Objectional Content on YouTube?

According to <a href="https://www.statista.com/statistics/1132956/share-removed-youtube-videos-worldwide-by-reason/">Statista</a>, YouTube removed 41 percent of content that jeopardizes child safety in the fourth quarter of 2020. Do you think a human can take on such a humungous task?No, right?That?s why this is done by Artificial Intelligence. Google uses machine learning systems to detect explicit content in all its platforms including YouTube. Scams, misleading information, <a href="https://cloud.google.com/video-intelligence/docs/analyze-safesearch">adult content</a>, violent content, and more are deleted after scanning.These contents take over a massive space on the web and result in social problems. Often people make hate speech on social media first. Uploading a video on YouTube is also a way people use to make explicit content.Recently, the threats of storming on U.S Capital were first made <a href="https://www.nbcnews.com/tech/internet/extremists-made-little-secret-ambitions-occupy-capital-weeks-attack-n1253499">online</a>.So, if Artificial Intelligence can detect such threats in time, it can keep the human community safe from any riot. However, it is not as easy as it seems. AI faces several challenges in detecting such contents.<h3 id="how-youtube-uses-artificial-intelligence-to-remove-objectional-content">How Youtube Uses Artificial Intelligence to Remove Objectional Content?</h3>There are more than 2 billion active monthly users on YouTube. Every minute, users upload <a href="https://merchdope.com/youtube-stats/">300 hours of videos</a> on the platform. This means a lot of objectional content too.YouTube has to use man force to remove such content. However, with the arrival of Artificial Intelligence, things changed. Although, there is a human specialist along with the machine at all times to inspect the work.The platform uses video classifiers to filter content on YouTube. Any video on this platform is only a stack of images but these images together convey a message. So, classifying the images in a video is not the best.However, this is how video classifier works. Here are a few steps of classifying videos using a classifier:1. The video file is set on a loop to detect all the frames.2. Each frame passes through CNN or convolutional neural networks (feature extractors)3. They are classified independently.4. The Frames are classified and labeled.For example, there is a boat in a frame, but the video is about swimming. Therefore, such videos require more than one label to identify the correct content in them. However, video-classifiers can also provide an idea about the whole content in the video.This is exactly how YouTube identifies explicit videos in its database. As soon as a video is uploaded on its system, it is stored in the data set. The video classifiers then work to find out what is the content type.If it matches with something that is labeled objectional, then the video is removed. However, this also causes errors. The classifiers can even remove news content with violent images.So, the artificial intelligence community has called the YouTube video classifiers ?<a href="https://www.digitalinformationworld.com/2019/05/google-trashy-video-algorithm-cleans-up-youtube-homepage.html">trashy</a>?.<h3 id="why-ai-specialists-disapprove-of-the-youtube-video-classifiers">Why AI Specialists Disapprove of the YouTube Video Classifiers?</h3>In 2018, YouTube removed 77% of videos from April to June even before they received a single view. However, some YouTubers are actively trying to fool the algorithm, which is not that difficult.For example, instead of using a racist term like 'African American' people started using 'Basketball Americans' to further genocide conspiracies and more. Many even resorted to using spelling errors to avoid algorithms detecting their content.The video classifier only scans the YouTube homepage and checks feedback from users to remove any explicit video. Even videos with misleading thumbnails or cuss words on them are removed.<h3 id="are-video-classifiers-helping-youtube">Are Video Classifiers Helping YouTube?</h3>The AI video classifiers are not full proof. However, before it came into the scene, YouTube could only<a href="https://www.forbes.com/sites/bernardmarr/2019/08/23/the-amazing-ways-youtube-uses-artificial-intelligence-and-machine-learning/?sh=583cc9b35852"> detect 8% of the content as violent or explicit</a>. From 8% it has went up to 83% which is a great feat.Moreover, Artificial Intelligence can flag the content <a href="https://www.weforum.org/agenda/2018/04/ai-is-now-youtube-s-biggest-weapon-against-the-spread-of-offensive-videos/">even before 10 views are completed</a>. Before 2017, YouTube could remove content only after it got 10 views.After the new mechanism rolled out, it also took down some of the news from Bellingcat and Middle East Eye. Those videos consisted of images from the Syrian war.However, <a href="https://www.middleeasteye.net/news/youtube-admits-wrong-call-over-deletion-syrian-war-crime-videos">YouTube later apologized</a> for deleting the war crime videos and other news about the civil war in Syria. Not only that, but a few news outlets found that their channels were suspended including Bellingcat.The incident occurred just after Google announced the use of AI on YouTube. The AI was unable to differentiate from news documents and videos and flagged them as "extremist". This led to the removal of this content."With the massive volume of videos on our site, sometimes we make the wrong call. When it?s brought to our attention that a video or channel has been removed mistakenly, we act quickly to reinstate it? Youtube told the news outlet.All the videos that got deleted were restored in the channel as before. However, it caused a lot of problems for the news outlets.<h3 id="why-removing-objectional-content-is-important">Why Removing Objectional Content is Important?</h3>There is constant pressure from Governments, brands, and the public to take down explicit videos from YouTube. It is because sometimes brand or Government ads show up on offensive videos. When such ads appear with such content, it creates a bad reputation for the brand.For example, after ads started appearing in videos supporting racism and terrorism, brands such as <a href="https://www.adweek.com/agencies/frustrated-with-ads-appearing-next-to-offensive-content-havas-pulls-u-k-spending-from-google-and-youtube/">Havas UK pulled their ad investments</a>.Sometimes, YouTube also recommends content that may be harmful to children. This led to a backlash from netizens. To counter this, YouTube came up with options that allows the creators to select whether a particular video is for children or not.However, this is not enough as the user may select the video for children option and upload the offensive content. The only way to fix this when any user reports it to YouTube. However, by the time someone identifies such content, it may have got a few views.Having objectional videos on the platform may cause aggression and riots. In the case of racist videos, things may turn worse. So, it's best to take down such videos.<h3 id="should-youtube-upgrade-its-ai-technologies">Should YouTube Upgrade its AI Technologies?</h3>From the various cases, it is evident that the video classifiers are not doing the trick. They act only on the home page. YouTube needs an algorithm that can deep search such contents, analyze them and remove them immediately.Although the AI which recommends videos are top-notch. They work according to the data collected from the user. Google collects every little data from the user. As Google owns YouTube, so it is easier to use those data to recommend.However, the recommendation of harmful content may cause more damage than good. So, YouTube must come up with AI that can remove such content.

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