AI in the Workplace and How It Supports Us

Over the last decade, there was significant fear that Artificial Intelligence (AI) will replace all humans at the workplace. However, those fears were totally unfounded, and today we work more efficiently and effectively, side by side, with smart algorithms.

According to IDC, enterprises across the planet will spend approximately $656 billion this year on future-of-work technologies. The bulk of that money will go towards AI-powered software for enterprise applications. As most of us will work remotely in the coming years, the industry will also focus more on overcoming challenges related to collaboration and productivity.

Let’s look at how AI is already supporting us at work, transforming how we get things done.

Smart algorithms are only as good as their training data sets. As such, it’s not surprising that algorithmic bias (or Bias in Artificial Intelligence = AI Bias) increasingly pops up when Artificial Intelligence (AI) and Machine Learning (ML) models go into production.

AI bias is dangerous because it could easily lead to poor decisions with disastrous consequences. I’m sure you have come across examples of AI bias in the news, like AI’s inability to recognize minorities and so on. So, it’s not hard to imagine businesses finding themselves in a legal nightmare.

How do you overcome or prevent AI bias?

SEO keywords: dead or alive?

Content, search intent, user experience, differentiated user signals, and artificial intelligence (AI) — Google’s ranking criteria are becoming increasingly complex. So where does that leave keywords? Have the keywords in the text outlived their usefulness as ranking factors? The relevance of keywords for search engine optimization has changed. Online copywriters are now facing new challenges.

Top 5 Common Training Data Errors and How to Avoid Them

In traditional software development, the code is the most critical part. In contrast, what’s crucial in artificial intelligence (AI) and machine learning (ML) development is the data. This is because AI training data models include multi-stage activities that smart algorithms must learn in order to successfully perform tasks .

In this scenario, a small mistake you make during training today can cause your data model to malfunction. This can also have disastrous consequences—for example, poor decisions in the healthcare sector, finance, and of course, self-driving cars.

So, what training data errors should we look out for, and what steps can you take to avoid them? Let’s look at the top five data errors and how we can prevent them.

Emotion Recognition – How computers see through our emotions

Emotion recognition or emotion detection is a method of detecting sentiments based on images, videos, audio, and text leveraging artificial intelligence (AI). In this scenario, technology uses data from different sources like photographs, audio recordings, videos, real-time conversations, and documentation for sentiment analysis.

Emotion recognition has become increasingly popular in recent years. In fact, the global emotion detection market is forecasted to grow to $37.1 billion by 2026.

Part of the “affective computing” family of technologies, the primary objective is to help computers or machines interpret human emotions and affective states. This is done by examining non-verbal forms of communication like facial expressions, sentence constructions, the use of language, and more.

Diary studies – valuable insights for marketing

According to an old saying, you can only find real truths in diaries. Modern market research makes use of this wisdom. A diary that relates to the use of a device, app or software can provide valuable insights for marketing. How do diary studies work and what makes them so successful?

Optimizing Your Business Site for Smoother Customer Experience

In 2021, there are anywhere between 12 to 24 million online shops across the internet, with more being created every day. With this amount of competition, online businesses must discover effective strategies to attract more customers and maintain their loyalty.

One crucial factor that affects your brand’s success is customer experience. A Walker study found that at the end of 2020, customer experience overtook price and product as the key brand differentiator.

This article will dive deeper into what customer experience is and its importance to your business. We will also take a look at nine ways to improve customer experience on your business website.

5 marketing tactics every eCommerce business should be using

If you’re working in eCommerce in 2021, you should be focusing on using the most effective digital marketing tactics in order to sell your products or services. In this article, we’re going to outline different tactics you can use to improve your sales. Let’s get started.

5 ways you can improve your SEO by boosting your site’s E-A-T

Search engine optimization (SEO) is a marketing strategy that helps you improve your website’s visibility and rankings on relevant search engine results pages. It’s a very important aspect of marketing that can help you reach your target audience and drive more traffic to your website.

One of the ways you can improve your site’s SEO is by enhancing its E-A-T and, in this article, we will look at how to do that.

How search results exactly match the search intention of the user

Have you ever wondered how search engines work? There are literally billions of web pages available online with millions more being created every year. Search engines do not only help you find a particular site, they also help find content and information within that site.

Consider the fact that search results need to work within a website also helping you find the specific “widget” you’re looking for so that you can make your purchase.