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Can AI Audits Eliminate Algorithmic Biases?

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Can AI Audits Eliminate Algorithmic Biases?


Algorithm bias may develop when AI is used to tackle global problems, resulting in unanticipated, wrong, and damaging outcomes.

AI bias is a problem that is becoming more prevalent as software becomes more integrated into our daily lives.

AI can sometimes manifest the same prejudices as humans, and it could be even worse in some circumstances. An aberration in the output of machine learning algorithms could be due to biases in the training data or prejudiced assumptions made during the algorithm building phase. Our society’s beliefs and standards have blind spots or certain expectations in our thinking. As a result, algorithmic AI bias is heavily influenced by societal bias.

How Does AI Bias Originate?

People are shaped by their upbringing, experiences, and society. They internalize certain beliefs about the world around them. It’s the same with AI. It doesn’t exist in a vacuum; it’s made up of algorithms created and refined by the same individuals. It tends to “think” or run algorithms in the same manner, it’s been taught. Whether conscious or unconscious, human prejudice lurking in AI algorithms throughout their development is the root cause of AI bias. Human biases and prejudices are adopted and scaled by AI solutions.

Auditing in Artificial Intelligence

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All the information and data collected by the AI algorithm are accessed and examined to see how these algorithms have performed, their outputs, and how they have computed things. In other words, what problem are they trying to solve, and what data do they have? Audits with access to an algorithm’s code can assess whether the algorithm’s training data is biased and create hypothetical scenarios to examine the impact on different populations.

Can Auditing Eliminate Algorithmic Bias?

The algorithms and data may appear neutral, yet their output reinforces societal biases. Artificial intelligence (AI) and machine learning have advanced rapidly, resulting in strong algorithms that have the potential to enhance people’s lives on a massive scale. Algorithms, particularly machine learning algorithms, are increasingly being used to supplement or replace human decision-making in ways that impact people’s lives, interests, opportunities, and rights. The ethical impact of AI has been extensively studied in recent years, with public crises involving lack of transparency, data exploitation and the proliferation of systemic racism. One of the few examples to explain AI bias would be Twitter’s photo cropping algorithm.

The quality of an AI system’s input data determines how good it is. You can design an AI system that makes unbiased data-driven decisions if you can clean your training dataset of conscious and unconscious assumptions about race, gender, and other ideological ideas. However, there are innumerable human biases. As a result, having a perfectly unbiased human mind and an AI system may not be attainable.

AI can assist us in avoiding discrimination in hiring, operations, customer service, and the more extensive business and social networks — and it makes excellent commercial sense to do so. Artificial intelligence can help us avoid harmful human bias – both intentional and unintentional. It is now evident that AI algorithms integrated into digital and social technologies can encode societal prejudices, speed the spread of rumors and disinformation, amplify echo chambers of public opinion, hijack our attention and even affect our mental welfare if left uncontrolled. AI bias can be avoided to a certain degree, but only if we educate it to play fair and continuously challenge the findings.    



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How Sports Organizations Are Using AR, VR and AI to Bring Fans to The Game

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How Sports Organizations Are Using AR, VR and AI to Bring Fans to The Game

AR, VR, and AI in sports are changing how fans experience and engage with their favorite games.

That’s why various organizations in the sports industry are leveraging these technologies to provide more personalized and immersive digital experiences.

How do you get a sports fan’s attention when there are so many other entertainment options? By using emerging technologies to create unforgettable experiences for them! Innovative organizations in the sports industry are integrating AR, VR and AI in sports marketing and fan engagement strategies. Read on to discover how these innovative technologies are being leveraged to enhance the game-day experience for sports fans.  

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AUGMENTED REALITY IN SPORTS

AR is computer-generated imagery (CGI) that superimposes digitally created visuals onto real-world environments. Common examples of AR include heads-up displays in cars, navigation apps and weather forecasts. AR has been around for decades, but only recently has it become widely available to consumers through mobile devices. One of the best ways sports organizations can use AR is to bring historical moments to life. This can help fans connect to the past in new ways, increase brand affinity and encourage them to visit stadiums to see these experiences in person. INDE has done just that, creating an augmented reality experience that lets fans meet their favorite players at the NFL Draft.

VIRTUAL REALITY IN SPORTS

VR is a computer-generated simulation of an artificial environment that lets you interact with that environment. You experience VR by wearing a headset that transports you to a computer-generated environment and lets you see, hear, smell, taste, and touch it as if you were actually there. VR can be especially impactful for sports because it lets fans experience something they would normally not be able to do. Fans can feel what it’s like to be a quarterback on the field, a skier in a race, a trapeze artist, or any other scenario they’d like. The VR experience is fully immersive, and the user is able to interact with the content using hand-held controllers. This enables users to move around and explore their virtual environment as if they were actually present in it.

ARTIFICIAL INTELLIGENCE IN SPORTS

Artificial intelligence is machine intelligence implemented in software or hardware and designed to complete tasks that humans usually do. AI tools can manage large amounts of data, identify patterns and make predictions based on that data. AI is already influencing all aspects of sports, from fan experience to talent management. Organizations are using AI to power better digital experiences for fans. They’re also using it to collect and analyze data about fan behavior and preferences, which helps organizers better understand what their customers want. AI is also changing the game on the field, with organizations using it to make better decisions in real time, improve training and manage player health. Much of this AI is powered by machine learning, which is a type of AI that uses data to train computer systems to learn without being programmed. Machine learning is the reason why AI is able to evolve and get better over time — it allows AI systems to adjust and improve based on new data.

MERGING THE REAL AND VIRTUAL

VR and AR are both incredible technologies that offer unique benefits. VR, for example, is an immersive experience that allows you to fully imagine and explore another virtual space. AR, on the other hand, is a technology that allows you to see and interact with the real world while also being able to see digital content superimposed on top of it. VR and AR are both rapidly evolving and can have a significant impact on sports marketing. By using both technologies, brands and sporting organizations can create experiences that bridge the real and virtual. This can help sports marketers create more engaging experiences that truly immerse their customers in the game.

Technologies like AR, VR and AI in sports are making it possible for fans to enjoy their favorite games in entirely new ways. AR, for example, can help sports lovers experience historical moments, VR lets them immerse themselves in the game, and AI brings them more personalized and immersive digital experiences. The best part is that sports fans can also use these technologies to interact with one another and feel even more connected. 

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The Dark Side of Wearable Technology

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The Dark Side of Wearable Technology

Wearable technology, such as smartwatches, fitness trackers, and other devices, has become increasingly popular in recent years.

These devices can provide a wealth of information about our health and activity levels, and can even help us stay connected with our loved ones. However, there is also a dark side to wearable technology, including issues related to privacy, security, and addiction. In this article, we will explore some of the darker aspects of wearable technology and the potential risks associated with these devices.

1. Privacy Concerns

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Source: Deloitte

Wearable technology can collect and transmit a significant amount of personal data, including location, health information, and more. This data is often shared with third parties, such as app developers and advertisers, and can be used to track and target users with personalized advertising. Additionally, many wearable devices lack robust security measures, making them vulnerable to hacking and data breaches. This can put users’ personal information at risk and expose them to identity theft and other cybercrimes.

2. Security Risks

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Source: MDPI

Wearable technology can also pose security risks, both to the individual user and to organizations. For example, hackers can use wearable devices to gain access to sensitive information, such as financial data or personal contacts, and use this information for malicious purposes. Additionally, wearable technology can be used to gain unauthorized access to secure areas, such as buildings or computer systems, which can be a major concern for organizations and governments.

3. Addiction Issues

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Source: Very Well Mind

The constant connectivity and access to information provided by wearable technology can also lead to addiction. The constant notifications and the ability to check social media, emails and other apps can create a constant need to check the device, leading to addiction-like symptoms such as anxiety, insomnia and depression.

4. Health Risks

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Source: RSSB 

Wearable technology can also pose health risks, such as skin irritation and allergic reactions caused by the materials used in the device. Additionally, the constant use of wearable technology can lead to poor posture and repetitive stress injuries, such as carpal tunnel syndrome. It is important for users to be aware of these risks and to take steps to protect their health, such as taking regular breaks from using the device and practicing good ergonomics.

Conclusion

Wearable technology has the potential to be a powerful tool for improving our health, fitness, and overall well-being. However, it is important to be aware of the darker aspects of wearable technology and the potential risks associated with these devices. By understanding the privacy, security, addiction, and health risks associated with wearable technology, users can take steps to protect themselves and their personal information. Additionally, by being aware of these risks, organizations can take steps to protect their employees and customers from the potential negative effects of wearable technology.

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Data Science & Machine Learning Trends You Cannot Ignore

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Data Science & Machine Learning Trends You Cannot Ignore

Digital transformation has become the new mantra for companies to thrive in the digital age.

Data science and machine learning are two major assets in the digital transformation era.

Digital transformation has become a necessity for businesses. It is the way forward for all businesses, regardless of size and scope. However, it should be more than simply digitizing your processes. Digital transformation should be about re-imagining your business processes with cutting-edge technology and artificial intelligence like data science and machine learning. This would help eliminate manual labor and accelerate growth with collaborative technologies like chatbots, virtual assistance and augmented reality, while having a seamless user experience across all channels – online, mobile app and website – with the help of an integrated CMS that can adapt to any screen size.

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With the above thoughts in mind, let’s look at four new DSML trends you cannot ignore.

Intelligent Automation

Most digital transformation initiatives focus on creating a digital front-end, with a strong focus on customer-facing channels. While that’s obviously important, a lot of organizations forget about the back-end and the data that’s being used by their systems. This is a mistake, as intelligent automation can help bridge the gap between the front-end and the back-end systems and processes. It’s a key element that can help organizations curate data, which is then used to enrich customer experiences and create personalized marketing campaigns, among many other things. An integrated CMS with an intelligent automation system can automatically pull customer data into content, provide real-time insights about customers and their behavior, and suggest personalized content for different channels.

Augmented Reality

Augmented reality lets you digitize your business processes by visualizing information. It can help you create exciting customer experiences by enabling them to see and interact with information in their physical environment. This technology has been used for gaming and entertainment for a long time, but now businesses are leveraging it for digital transformation. With augmented reality, you can create interactive product catalogues, digital manuals and helpful visual guides to engage customers and employees.

Chatbots and Voice Recognition

Digital transformation is about more than just creating engaging customer experiences; it’s also about making sure that those experiences are accessible on any platform. Coupled with voice recognition, chatbots can be used across all customer channels, including websites and apps, to provide information, schedule appointments, and answer basic questions. A key element of digital transformation is making your business accessible to customers no matter where they are or what device they’re using.

Unified Experience Across Devices

A unified experience across devices ensures that customers experience the same content and functionality regardless of what platform they’re using. For example, let’s say a customer wants to learn more about your product. With a unified experience across devices, the customer would be able to access information about the product from their computer or mobile device. This way, if a customer is on the go and has limited screen real estate, they can still access the information they need.

 

A digital transformation is necessary for businesses to grow and thrive. However, it takes more than just digitizing processes. With the help of data science and machine learning, organizations can reimagine how they work with new technology and tools. Thereby, they can create an integrated experience across devices and channels, with a seamless flow for customers and employees.

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