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Google Will Now Let Users Remove Sensitive Personal Information From Search Results

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Google Will Now Let Users Remove Sensitive Personal Information From Search Results

Google seriously cares about the personal information of its users.

The company has a long history of developing Internet security technology that benefits its own users and the online world as a whole.

Over the years, it has become increasingly challenging to keep personal information off the web — but thanks to Google’s updated policies, users are now able to take more control of their online presence in search by heading to the Google support section and clicking on remove personal information.

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Google users can now request personal information — such as phone numbers, email addresses and home addresses — to be removed from search engines. The policy expansion also enables people under the age of 18, or their parents or guardian, to request the removal of their images from Google Search results.

According to Google, being able to request the removal of personal information from the web for safety purposes isn’t a new feature.

For many years, people have been able to request the removal of certain sensitive, personally identifiable information from Search, per the blog post. This applies to cases of doxxing — when personal info, like addresses, are shared publicly with malicious intent — or for information like bank account or credit card numbers that could be used for financial fraud.

Google is making it possible for you to protect your personal information further by allowing removal requests for additional types of information that may pose a risk for identity theft, such as confidential log-in credentials, when it appears in Search results.

Once your request is submitted, you’ll get an automated email confirming your request. 

Please note that Google may ask for additional information: for example, a web address if there’s one missing from the original request submission.

When all of the information is submitted and the request has been processed, Google will notify you of any action taken in regard to your request.

It’s important to state Google may deny a removal request if it’s public utility information. 

When Google receives removal requests, they will “evaluate all content on the web page” to ensure that they’re not “limiting the availability of other information that is broadly useful, for instance in news articles.” Additionally, if the content appears as a public record on the sites of government or official sources, they won’t proceed with the removal.


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Four Cutting-Edge Technologies That Enhance User Experience

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Four Cutting-Edge Technologies That Enhance User Experience

The Future of UX Design: Four Cutting-Edge Technologies That Enhance User Experience

At the dawn of the computer age, PCs did not have a graphical user interface.

Only employees of scientific institutions could work with them. With the help of special commands, they accessed an operating system through a console. In the 1970s, Xerox PARC managed to make technology clear for people by developing a GUI. The era of personal computers began. Nowadays, it is hard to amaze users who have already seen iOS, Android, MacBook, and Apple Watch with previous computer achievements. User experience does not stand still, and innovations that challenge UX design constantly appear. Let’s take a look at four promising UX design techniques. 

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1. Voice User Interface 

In his book The Design of Everyday Things (the “bible” of usability), Professor Don Norman states the main goal of UX/UI designers. They need to provide users with pleasant and simple product experience. Designers should always put themselves in the client’s shoes and solve their problems most conveniently.

At present, an average user needs a keyboard, mouse, or touch screen to work with an application interface. However, the future of devices is often seen as interfaceless. Golden Krishna has written a book on this topic called The Best Interface Is No Interface: The Simple Path to Brilliant Technology. But is it possible to work without an interface? Yes, you can easily do it with the help of voice and virtual assistants like Amazon Alexa, Google Home, Siri, and others.

In 2019, there were 2.45 billion voice assistants. By 2023, their number will equal the number of people in the world and will be approximately 8 billion. VUI is a hot trend in design, and IT professionals need to learn how to build efficient voice interfaces.

A voice interface does not have a visual representation. Therefore, the main task of designers implementing a VUI solution is to research the target audience, its goals and pains, develop interaction scenarios with a voice device, and prepare a text message from the user and device responses.

Designers need to analyze how clients will interact with a device and determine what they may need a VUI for. They need to collect terms and phrases that customers use more often. This data will be useful to build conversations between a person and a device.

Then they should consider scenarios for using the VUI and make sure that the voice assistant solves the problem most simply and efficiently. For example, if a person asks an assistant for a route from Chicago to New York, the device must understand the request and provide the necessary information in the correct context. Voice interaction should be constantly improved in each design iteration so that smart assistants recognize speech and its meaning correctly.

After working with dialogs, designers need to develop a voice interface, test it and continue to improve it. If everything is carried out correctly, a business will gain a competitive advantage over companies that have not embedded voice assistants into their applications.

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2. Touchless Gesture Control

Previously, people needed styluses and touch screens to work with smartphones. But in the future, users won’t need to touch their phones at all to turn on music, answer a phone call, or increase the volume. In 2015, Google presented its Soli technology by introducing a miniature radar reading every human movement.

Since then, designers have been talking about touchless gesture control, a new way of human interaction with devices and applications. Examples of this are the Google Pixel 4 smartphone and the Airtouch dashboard from BMW. The latter allows drivers to change the volume of music or receive calls without taking their eyes off the road.

What does this innovation mean for designers? UX/UI professionals need to think about navigation, action, and transformation gestures that will allow them to control the content of devices. The movements must correspond to the ergonomics of the human body, be simple and not require great physical effort. The design community hasn’t yet developed common gestures for UX, so you can create your own. You can base it on real-life experience and make it as simple as possible to reproduce.

Users must be provided with textual or visual hints allowing them to learn a sign language. Also, do not forget about people with disabilities who may have problems with fine motor skills. Therefore, designers should also implement an alternative interface, with the possibility to connect joysticks or electronic devices. 

Touchless gesture control opens up a new accessible user experience for customers, building unique ways of interacting with an application.

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3. Artificial Intelligence

AI is widely used to create voice assistants. A smart algorithm can also optimize the work of UX designers.

Personalization is the queen of UX. McKinsey estimates that 71% of consumers expect firms to have a personalized experience, and companies that succeed in it increase revenue by an average of 40%. To provide a personalized experience, IT professionals need to analyze a huge amount of user data, then segment it and provide customers with relevant content only. AI is extremely helpful in analytics. Using archive data, the algorithm predicts a user action or request and suggests the best UX option to a designer. Thus, AI in UX allows you to optimize interface modules, present an improved experience and increase the value of a product for a wide audience.

AI in UX will automate repetitive simple designer tasks. For example, it can perform color correction and photo resizing, while a UX specialist solves more important tasks. Of course, AI developers have impressive ideas. They want to teach a smart algorithm to understand sketches and turn them into user interfaces. By the way, this feature has already been implemented in a designer assistant, an application based on AI Uizard.

Content generators for design layouts are built on AI. A designer usually needs a lot of time to fill in text and photos to create content that is close to reality. Generative adversarial networks use a smart algorithm to automatically fill layouts with real content. There are similar solutions on the market. Take, for example, the This Person Does Not Exist platform which generates photos of non-existent persons based on images of real people. Such software already frees UX designers from certain tasks and responsibilities, allowing them to devote all their attention to perfecting layouts.

4. Virtual Reality

As science advances, VR/AR/MR in UX are actively penetrating healthcare, education, eCommerce, and other industries. According to researchers, in 2021, these technologies cost $28 billion. By 2028, they are predicted to grow to $250 billion. This is a powerful trend that UX designers cannot disregard.

Designers follow the same pattern when implementing VR solutions. They research the customer and the target audience to create UX. The difference is that in VR applications, the client is not a bystander but an active participant. To plan digital interactions for these applications, specialists should use the storyboard technique and get their ideas down on paper first.

It is also important to consider the duration of a VR session. As a rule, it does not exceed 20-30 minutes because people get tired and lose concentration. If a session in a VR application lasts longer, designers should consider the option of saving the progress and returning to it afterward. A UX designer needs to correctly calculate the scale of the VR space so that users do not get lost in an environment that is too large or does not experience discomfort in a small area.

It is important to consider the VR space issues that prevent the most common problem – motion sickness. To do this, you can create fixed points in space or a static horizon that remain motionless while a user moves. Thus, the person can focus on something so as not to feel dizzy. Designers should also take care that the user keeps the same speed, there are no sharp drops, and there are “staging posts” for rest. Sound accompaniment corresponding to the actions taking place in virtual space will also help a person avoid disorientation and motion sickness.

For a convenient adaptation of users to VR, specialists need to consider a system of hints that guide customers along the way. They should avoid using too much text: in a virtual environment, excessive reading provokes eyestrain. It is better to add audio instructions, visual effects, and simple sentences to convey important information. Users will be grateful for such care.

Conclusion

UX design technologies improve the customer experience by providing users with new opportunities and more convenient interactions with applications. UX designers have to adapt to new trends to offer clients an easier and more inspiring way to solve problems. As you can see from the examples above, VUI, touchless gesture control, AI, and VR do a good job of UX tasks. For a professional designer, knowledge of these technologies is a must. For a business, they mean an opportunity to increase revenue through an improved CX.

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Why Decision Intelligence Is Important

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Why Decision Intelligence Is Important

Traditional decision-making techniques will lose effectiveness as firms become more complicated.

Tech leaders must use decision intelligence models to enable exact and contextualized decisions.

Because it is difficult to identify potential disconnections associated with behavioral models in a commercial environment, many current decision-making models need to be more logical. With the aid of machine learning and AI algorithms, decision intelligence may help organizations make better decisions. Decision intelligence is the use of automation and machine learning to support human judgments in order to make business judgments that are more accurate and swift.

To do this, decision intelligence gives anyone the tools to ask and respond to ‘what, why, and how’ kinds of questions of unaggregated data, significantly decreasing the time and effort required to develop strategic, operational decisions. Employing decision intelligence promotes automation without undervaluing the importance of human judgment, expertise and intuition. However, businesses must persistently work to increase their daily operations’ productivity and eradicate bias in their decision-making processes. By utilizing data analytics, artificial intelligence and machine learning for precise decision-making, decision intelligence can assist businesses in accomplishing more with less.

Why Decision Intelligence Is Important

Decision intelligence becomes extremely important as it enables businesses to make accurate decisions. Below are a few pointers of decision intelligence that make it a critical decision-making tool for businesses to succeed.

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To Rethink

Today’s work is frequently dull and unfulfilling, negatively affecting productivity and happiness. Due to the time saved by decision intelligence, businesses will eventually need to stop defining people by their employment and think about decreasing dull work. This will enable them to produce more purposeful, original and creative work.

To Redefine

Decision intelligence is changing the way we learn and think. Analyzing data, gaining insights, creating forecasts, and assisting in decision-making are all aspects of thinking and learning skills. By combining and unlocking the distribution of distinctive information, data intelligence frameworks help to redefine and increase the breadth of end-to-end business workflows.

To Reinvent

Data intelligence will be highly crucial and beneficial for businesses to strengthen their competitive edge, develop detailed customer segmentation, anticipate market needs, and develop customer-centric strategies. Thereby, it can assist businesses in reinventing new customer acquisition business models.

To Repurpose

A data-driven environment with a technology base that enables organizations to synthesize information, learn from it, and apply insights at scale can be built by firms through leveraging decision intelligence. This will accelerate decision-making, increase agility and resilience and develop a business culture that supports organizational-driven initiatives with a purpose.

 

Decision intelligence does not eliminate human judgment from the decision-making process. Instead, it is vital to equip humans with AI and a more comprehensive, approachable perspective of all the data pertaining to their businesses so that they can make effective business decisions. It allows businesses to process and forecast data in order to make more educated decisions at every level of the organization. Additionally, it assists organizations in gaining better visibility into their operations and producing game-changing business results. Furthermore, with tons of data insights to consider in the decision-making process in this digital era, the next stage of digital transformation will involve having assistance in making wise decisions. Decision intelligence will enable businesses to deliver predictive outcomes as data and insights become more crucial.

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NLP & Computer Vision in Cybersecurity

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NLP & Computer Vision in Cybersecurity

Natural language processing (NLP) and computer vision are two branches of artificial intelligence (AI) that are disrupting cybersecurity.

NLP is the ability of computers to understand and process human language, including speech and text. In cybersecurity, NLP can be used for fraud detection by analyzing large amounts of text data, such as emails and chat logs, to identify patterns of malicious activity. NLP can also be used for threat intelligence by analyzing data from various sources, such as news articles and social media, to identify potential security threats.

Computer vision, on the other hand, refers to the ability of computers to interpret and understand images and videos. In cybersecurity, computer vision can be used for password cracking by analyzing images and videos that contain passwords or other sensitive information. It can also be used for facial recognition, which verifies the identity of individuals who access sensitive information or systems.

Cybersecurity is a critical issue in our increasingly connected world, and artificial intelligence (AI) is playing an increasingly important role in helping to keep sensitive information and systems secure. In particular, natural language processing (NLP) and computer vision are two areas of AI that are having a major impact on cybersecurity.

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Source: Masernet

NLP and computer vision have the potential to revolutionize the way organizations approach cybersecurity by allowing them to analyze large amounts of data, identify patterns of malicious activity, and respond to security threats more quickly and effectively. However, it’s important to be aware that AI itself presents new security risks, such as the potential for AI systems to be hacked or misused. As a result, organizations must adopt a comprehensive and well-informed approach to cybersecurity that takes into account the full range of risks and benefits associated with AI technologies. Here are 4 ways NLP & computer vision are useful in cybersecurity.

1. Detecting Fraud

NLP can be used to analyze large amounts of text data, such as emails and chat logs, to identify patterns of fraud and other types of malicious activity. This can help organizations to detect and prevent fraud before it causes significant harm.

2. Analyzing Threats

NLP can also be used to analyze large amounts of text data from a variety of sources, such as news articles and social media, to identify potential security threats. This type of “big data” analysis can help organizations to respond to security threats more quickly and effectively.

3. Preventing Password Cracking

Computer vision can be used to crack passwords by analyzing images and videos that contain passwords or other sensitive information. This type of technology can help organizations to better protect their sensitive information by making it more difficult for attackers to obtain passwords through visual means.

4. Improving Facial Recognition

Computer vision can also be used for facial recognition, which can help organizations to improve their security by verifying the identity of individuals who access sensitive information or systems.

Conclusion

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Source: Visua

AI technologies like NLP and computer vision are playing an increasingly important role in helping to keep sensitive information and systems secure. These technologies have the potential to revolutionize the way that organizations approach cybersecurity by allowing them to analyze large amounts of data, identify patterns of malicious activity, and respond to security threats more quickly and effectively. However, it’s also important to recognize that AI itself presents new security risks, such as the potential for AI systems to be hacked or misused. As a result, organizations must take a holistic and well-informed approach to cybersecurity that takes into account the full range of risks and benefits associated with these powerful new technologies.

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