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The Role of AI and ML in Improving Digital Performance

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By Anil Gupta

Artificial intelligence and machine learning are among the top marketing buzzwords we come across in the field of digital marketing. These technologies have already become an integral part of digital marketing and are being leveraged to make campaigns more personable and efficient.

For instance, artificial intelligence can make personalization easy and quick by creating accurate buyer personas. These personas are auto-generated to deliver a holistic audience segmentation, thereby improving the effectiveness of the campaigns. In addition, Netflix, Google, Uber, Spotify, Pinterest, and other apps use machine learning to personalize individual accounts and make relevant recommendations to their users.

The ever-improving algorithms and the exponential growth of data are encouraging business leaders and marketers to use AI, in the form of machine learning, natural language processing (NLP), deep learning, and other technologies. These technologies are helping them improve customer experience and conversions.

A Gartner survey shows that 37% of organizations are applying AI in some form or the other to boost their digital performance.

This post highlights how AI and ML are proving to be game-changers in the digital marketing realm.

1. Offer a Better Understanding of the Audience

Great content starts with knowing the audience well. When a business knows its target audience, the connection feels more natural and relevant. That genuine connection goes a long way in building lasting relationships with customers.

In recent years, AI and ML have opened up a whole new world of possibilities for understanding audience behavior. AI tools and data-driven insights are helping businesses understand who they are reaching, what the customers want and need, when to communicate, and where to reach them.

Artificial intelligence helps marketers instantly define buyer personas. Then, platforms like Socialbakers auto-generate these personas to deliver more holistic audience segmentation in the form of actionable insights. These insights help content marketers share inspiring stories that convert.

Keeping your audience at the centre of your online strategies is critical to business success. AI can help by offering unique audience insights, enabling businesses to deliver an integrated brand experience through relevant content. It also helps in selecting the most trustworthy and effective influencers for the brand.

2. Help with Lead Management

Big data, predictive analytics, and machine learning are being increasingly used in business intelligence these days. Machine learning, with its ability to bring out valuable hidden insights from large data sets, can create tangible value for businesses.

Leads are the driving force for businesses. They are the ones who will soon contribute to the organizational revenue. Hence, business leaders spend a significant amount of time in lead management. ML can be leveraged to improve and scale a firm’s approach to lead management, thereby boosting the bottom line. It helps firms generate better leads, qualify and nurture them, and ultimately monetize them effectively.

For instance, ML can help you create an ideal customer profile (ICP) to reach the best customers. ICP takes a structured look at the demographics and psychographics of an individual and determines their purchase intent and the content that matters to them. Thus, ICP can be used for lead scoring, allowing marketers to prioritize targeted accounts.

ML can also help firms generate more qualified leads from the traffic already coming to the site. For example, check out how Drift, a revenue acceleration platform, uses conversational AI to recognize quality from noise, learn from the conversations, and automatically qualify or disqualify website visitors. These qualifiers help the sales team focus on leads that are ready for conversions.

3. Curate and Create Better Content

AI is changing the game for content marketers. The technology is being used to automatically generate content for simple stories like sports news or stock market updates. AI also allows social channels to customize user new feeds.

But one content field where AI is increasingly applied is content curation. AI algorithms make it easier to collect target audience data to create relevant content at each stage of the marketing funnel.

For instance, the algorithms collect data on what the audience prefers to read, the questions they want answers to, or any specific concerns. Using this data, content marketers can curate and create relevant content that boosts customer experience and ultimately leads to conversions.

The North Face uses an AI-powered technology like IBM Watson that recreates shopping experiences. The AI tool uses cognitive computing that brings the online and in-store experiences closer together.

Besides, machine learning feeds content strategies by discovering fresh research-based content ideas, identifying the top-performing topic clusters, showing the most relevant keywords in a specific niche.

For instance, Google Analytics and SEMrush operate on machine-learning algorithms that are useful in keyword research and discovery, and content distribution. In addition, these tools can discover industry trends and show you ways to rank higher in SERP.

AI and ML-enabled tools improve the overall reception and performance of online content. In addition, the tools allow marketers to offer relevant and personalized digital experiences that positively influence engagement.

4. Help with Competitive Search Engine Ranking

Search engines are already using AI-enabled algorithms to deliver the most relevant SERP results. These algorithms rely on AI to understand the context of the content and spot irrelevant keywords. No wonder SEOs are constantly striving to understand these algorithms and coming up with strategies to create contextual, conceptual, and accurate content.

The placement of your business in the SERPs can make or break your online reputation and performance. AI technologies make it easier to create compelling content that answers the target audience’s queries, keywords, and phrases.

SEO isn’t a day’s job. It’s challenging, and the results of one’s efforts can only be seen after months. Fortunately, AI-based SEO tools help alleviate this stress. SEO optimization tools like Moz, WooRank, BrightEdge, and MarketMuse heavily rely on AI to offer SEO solutions like:

  • Keyword research
  • Search terms to make the content more relevant
  • Link-building opportunities
  • Trending topics
  • Optimum content length
  • User intent and more.

Tools like Alli AI can instantly optimize your website regardless of the CMS and your web development expertise. The platform performs a site-wide content and SEO audit, automatically optimizes the content, and resolves duplicate content issues. All this makes it easier for content creators to avoid poor-performing content and boost their online ranking.

5. Improve Page Speed

Google has put an exact value on fast user experience by including page speed as one of its ranking signals. That’s why boosting page speed is one of the top priorities for all businesses, especially ecommerce firms. As a result, Webmasters take all sorts of measures to improve page speed.

For instance, WordPress site owners may speed up WordPress by optimizing background processes, keeping the WP site updated, using a content delivery network (CDN), or using faster plugins. Of course, they also use various tools like Page Speed Insights, load time testers, and CMS plugins for the purpose. But now, there’s another ML-powered solution available for boosting the page speed – the Page Forecasting Model.

This model predicts user behaviour using machine learning and predicts the next page visitors will click on in real-time. This allows Webmasters to preload the page in the background, thus improving the overall experience.

The algorithm is trained with historical data from Google Analytics.

For instance, user patterns like going from home page to category page or product page to the shopping cart are recognized, understood, and included in update algorithms. If the user behaves similarly, the algorithm is automatically prepared with the next page.

However, the prediction accuracy is dependent on the amount of data available to train the algorithm and the website structure. So, the models will vary according to these factors. For instance, if yours is an ecommerce website that combines industry news with product pages, it’s better to use two or more models that can predict the behaviour per section.

6. Automate Website Analytics Process

Web analytics isn’t new. Businesses have been assessing user behaviour and tracking key performance metrics since the mid-’90s. But thanks to AI and machine learning, web analytics tools now have robust capabilities that allow businesses to automate the process. These tools can offer auto-generated reports and on-demand insights that feed marketing strategies.

Within a single visit to a webpage, each user generates hundreds of data points like the time spent on a page, the browser details, its location, and others. It is practically impossible to analyse all this data manually. AI and ML make such analysis faster and accurate by speeding up the data processing.

AI-based tools can help you track each visitor’s online behaviour, understand user journeys, and how customers move through the marketing funnel. They also point out issues, if any.

Let’s say you have a blog post that gets a lot of traffic, but visitors just read the post and leave without taking action like subscribing to your newsletter or sharing your post on social media. AI-based tools can flag such issues, allowing you to take the necessary corrective action like adding internal links or improving your CTA.

Google Analytics (insights section), Adobe Analytics, and Kissmetrics are among the top web analytics tools that help firms see patterns in customer behaviour and predict future trends.

7. Improve Site Navigation

Site navigation is another critical area in digital performance where AI and ML can help is site navigation. Though it may sound negligible, the importance of having organized and easy-to-follow navigation cannot be ignored. Well-planned navigation improves the visit duration, reduces the bounce rate, and boosts user experience. It also enhances the overall aesthetic appeal of the website design.

AI can help Webmasters create a user-friendly website structure that’s easy to navigate. AI-powered chatbots can guide users through the pages and help them find what they are looking for within the first few clicks. This significantly improves the user experience and sends good signals to search engines, indicating that your content is useful and relevant.

Thus, Google and other search engines will rank your page higher than any other website offering similar content.

8. Design Better Websites

AI applications can improve the usability and experience of a website by enhancing the site’s appearance, strengthening its search abilities, managing inventory better, and improving interaction with website visitors. No wonder a growing number of designers and developers are moving towards AI-based design practices.

AI is slowly becoming an indispensable part of modern web design and development. Take the field of artificial design intelligence (ADI) systems, for instance. ADI has triggered a sudden shift in the way web designing is done. It allows designers to combine applications into the website for better user experience and functionality.

Check out The Grid website platform that automatically adapts its design to highlight the content. The platform uses ML and constraint-based design and flow-based programming to dynamically adapt the website design to the content.

Today, we have several entrants in this space that are taking AI in web design to a whole new level. Brands like Adobe, Firedrop, Bookmark, Wix, Tailor Brands, and many others are leading the segment and leveraging the capabilities of AI in web design. In addition, most of these ADI platforms can learn and offer suggestions for optimizing the website for better user experience and SEO performance.

The Way Forward

Artificial intelligence and machine learning are proving to be awesome technologies when it comes to improving a firm’s digital performance. However, it is essential to remember that these ML models are only as good as the data that’s used to train them. Therefore, it’s critical to ensure that your marketing team has access to high-quality and accurate data.

So, before applying these technologies to your digital efforts, there are specific steps that you need to take.

  • Set up tags to track and capture on-site user behaviour.
  • House all the data from different sources in one central place like Google BigQuery, a Big Data analytics platform.
  • Invest in data deduplication to eliminate duplicate copies of repeating data from multiple sources.

Once your data is in place, you will be in a great position to start deploying AI and ML for boosting your digital performance. In addition, the information shared above will prove to be useful as you start building machine learning solutions for improving your business’s online presence.

By Anil Gupta

Anil is the CEO & Co-Founder of Multidots, one of the top WordPress development agencies on the planet. He is a technopreneur with over 13 years of experience coding, thinking, and leading the business with mind and people with heart. He and his team are seasoned in delivering secure and feature-reach WordPress services for businesses big and small.

Sourced from readwrite

 

 

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7 Tips to Use AI to Acquire and Retain Customers

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By Kevin Payne

Artificial Intelligence (AI) mimics the cognitive functions of the human mind, particularly in learning and problem-solving. Many of the apps that we use today are powered by AI. From voice-activated virtual assistants to e-commerce, AI applications are everywhere.

With the advancements in AI technology and access to big data, companies across different industries are integrating AI into their processes to find solutions to complex business problems.

The application of AI is most noticeable within the retail and e-commerce space. Websites and apps can interact intelligently with customers, creating a personalized approach that enhances the customer experience.

No matter what industry your business operates in, these seven tips can help you acquire and retain customers more efficiently at a fraction of the time it takes to do things manually.

How to Use AI to Get and Keep Customers

1. Identify Gaps in Your Content Marketing Strategy

If you’re just starting with content marketing, you’ll need to know what type of content to create.

By using AI, you can identify the gaps, find fixes, and evaluate the performance of your content marketing campaign.

Take Packlane, a company that specializes in custom package designs, for example. They came up with high-quality content like helpful blog posts that provide valuable information. At the same time, the content they publish makes it easier for their target market to understand their brand and services.

If you’re in the retail or e-commerce space, you can use AI to identify the gaps in your content marketing. Your content may be focused on your products and their features, but through AI, you can determine the relevant content that addresses your audience’s needs and pain points.

2. Pre-Qualify Prospects and Leads

Not every visitor to your site will become a paying customer. If you’re not getting sales despite the massive traffic, it means you’re generating low-quality leads.

Some reasons why this happens includes:

  • Targeting the wrong audience
  • Poor content marketing strategy
  • Using the wrong type of signup form
  • Promoting in the wrong social media platforms
  • Ineffective calls to action

These explain why 80% of new leads never convert into sales. The mistakes can be rectified with the help of artificial intelligence.

AI tools can extract relevant data to help you learn more about your target audience. These tools also provide predictive analytics on your customers’ behaviour. They, in turn, help improve your lead generation strategy because you’ll know which leads to pursue, where to find them, and how to effectively engage them.

3. Provide Personal Recommendations

According to a report by the Harvard Business Review, even though there are privacy concerns when consumers’ personal information changes hands, people still value personalized marketing experiences.

Brands that tailor their recommendations based on consumer data boost their sales by 10% over brands that don’t.

Recommendation systems’ algorithms typically rely on data on browsing history, pages visited, and previous purchases. But AI is so advanced that it can analyse customers’ interactions with the site content and find relevant products that will interest the individual customer. This way, AI makes it easier to target potential customers and effectively puts the best products in front of the site visitors.

Because of AI, recommendation engines are able to filter and customize the product recommendations based on each customer’s preferences. It’s a cycle of collecting, storing, analysing, and filtering the available data until it matches the customers’ preferences.

This is an effective way of acquiring and retaining customers because there’s an element of personalization.

4. Reduce Cart Abandonment

A high cart abandonment rate is the bane of e-commerce business owners. According to a study by the Baymard Institute, online shopping cart abandonment rate is close to 70%.

Users abandon their online carts for various reasons:

  • high extra costs
  • complicated checkout process
  • privacy concerns
  • not enough payment methods, or
  • they’re not ready to buy yet.

Using AI-powered chatbots is one way to reduce cart abandonment. AI chatbots can guide the customers through their shopping journey.

AI chatbots can have a conversational approach and give the customer a nudge to prompt them to complete the purchase. These chatbots can also act as a virtual shopping assistant or concierge that can let a customer know about an on-the-spot discount, a time-sensitive deal, a free shipping coupon, or any other incentives that will encourage them to complete the checkout.

With AI, lost orders due to cart abandonment are recoverable and can lead to an increase in conversion rate for e-commerce businesses.

5. Increase Repurchases With Predictive Analytics

Predictive analytics is the process of making predictions based on historical data using data mining, statistical modelling, artificial intelligence, machine learning, and other techniques. It can generate insights, forecast trends, and predict behaviours based on past and current data.

In marketing, predictive analytics can be used to predict customers’ propensity to repurchase products as well as its frequency. When used to optimize marketing campaigns, AI-powered predictive analytics can generate customer response, increase repurchase, and promote cross-selling of relevant products.

It’s all part of the hyper personalized marketing approach, where brands interact and engage with customers and improve their experience by anticipating their needs and exceeding their expectations.

With predictive analytics, you can focus your marketing resources on customer retention and targeting a highly motivated segment of your market that are more than happy to return and repurchase your products. This approach is less expensive than advertising or implementing pay-per-click campaigns.

6. Improve Your Website User Experience

Every business—big or small—knows the importance of having a website, where visitors can interact with the brand, respond to a call to action, or purchase products. But it’s not enough to just have an online presence; it’s important that visitors to the site have a great experience while navigating through your site.

What makes for a great user experience? Users have different expectations. Some of them want faster loading time, while others want a simple and intuitive interface. But most important of all, they want to find what they’re looking for. It could be a product, content, or a solution to a problem. Whatever they may be, it’s up to you to meet their expectations.

With artificial intelligence, you can improve your website user experience tenfold. Here are some of the ways AI can be used to improve user experience.

Search relevance

This pertains to how accurate the search results are in relation to the search query.  The more relevant the results are, the better search experience the users will have. This means they are likely to find relevant content answering their queries or finding products that solve their problems.

Personalized recommendations

Content that is tailor-made for the user tends to have greater engagement which increases the likelihood of conversation. Amazon has perfected the product recommendation system using advanced AI and machine learning. AI gets data from customers and uses it to gain insights and apply predictive analysis to recommend relevant products for cross-selling opportunities.

AI chatbots

The presence of chatbots contributes to a great user experience because they provide 24/7 assistance and support in the absence of human customer service.  Users can get accurate answers to their inquiries quickly and efficiently, compared to scrolling through a text-based FAQs.

7. Social Listening for Potential Customers

Social listening is the process of analysing the conversations, trends, and buzz surrounding your brand across different social media platforms. It’s the next step to monitoring and tracking the social media mentions of your brand and products, hashtags, industry trends, as well as your competitors.

Social listening analyses what’s behind the metrics and the numbers. It determines the social media sentiment about your brand and everything that relates to it. It helps you understand how people feel about your brand. All the data and information you get through social listening can be used to guide you in your strategy to gain new customers.

Social media monitoring and listening can be done much more efficiently with the help of artificial intelligence. It’s an enormous task for a team of human beings to monitor and analyse data, but with AI-powered social media tools, all the tedious tasks can be automated. They can be trained to leverage data to provide valuable insights about your brand with high accuracy.

With AI and machine learning, your social listening can easily determine your audience, brand sentiments, shopping behaviour, and other important insights. By having this information within reach, you’ll know how you can connect with them more effectively and turn them from prospects to paying customers.

Key Takeaways/Conclusion

More companies across different industries are using the power of artificial intelligence and machine learning to significantly increase brand awareness, enhance customer engagement, improve user experience, and meet customer expectations.

  • AI can identify gaps in your content marketing strategy so that you can create content that’s relevant to your target audience.
  • AI can help you generate high-quality leads that are likely to buy your products.
  • With AI, you can personalize and tailor-fit your product recommendations based on your customers’ preferences, increasing repeat purchases.
  • AI can be integrated into your e-commerce site to reduce shopping cart abandonment.
  • AI significantly improves website user experience by making it intuitive, accessible, and easy to navigate.
  • AI-powered social media tools can help you monitor and gain valuable insights about your brand. You can then use this to develop a social media marketing strategy to gain new customers.

Achieve these milestones, and you’ll be sure to acquire new customers and retain existing ones.

Feature Image Credit: iStock/monsitj

By Kevin Payne

Sourced from Black Enterprise

 

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Social media influencer/model created from artificial intelligence lands 100 sponsorships

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Sourced from allkpop

With the advancement of technology, AI influencers and virtual human models are becoming the new trend. It has recently emerged as a blue-chip in the advertising industry because there are no privacy scandals and there are no time-space restrictions with these virtual humans. In particular, the use of virtual humans seems to be gaining more momentum in the COVID-19 pandemic, where there are many restrictions on travel and limitations on the number of people gathering.

On September 10, Baek Seung Yeop, CEO of Sidus Studio X that created ‘Rozy,’ the newly rising blue-chip in the advertisement industry, explained, “These days, celebrities are sometimes withdrawn from dramas that they have been filming because of school violence scandals or bullying controversies. However, virtual humans have zero scandals to worry about.” 

‘Rozy’ is a virtual human that was created Sidus Studio X last year in August. Her age will forever be 22, and she has been keeping an active presence online as a real human since December of last year. In particular, this virtual human began gaining much attention as she appeared in an advertisement for Shinhan Life in July.

According to CEO Baek Seung Yeop, Rozy currently has advertising contracts with companies and a significant amount of sponsorships. CEO Baek said, “We have advertised twice already this week alone and now we have eight exclusive contracts,” and continued to explain, “She has landed more than 100 sponsorships now, but we have not been able to process them yet.”

He then added, “We have achieved our goal profit now, and I think Rozy will be able to make more than 1 billion KRW (~$854,007) by the end of this year.”

In regards to Rozy’s visual, CEO Baek explained, “We didn’t use a specific person as the model to her look. The MZ generation does not like to hide their flaws nor reveal their flaws. We didn’t take western beauty as the beauty standard either.”

CEO Baek Seung Yeop also shared Rozy’s future plans. He explained that the company plans to expand Rozy’s scope of activities, moving on to movies, dramas, and entertainment shows.

As CEO Baek said, the reason for the popularity of virtual humans is that there is no fear that advertisements will be suspended due to unsavoury privacy scandals after the AI model is selected as the advertising model. In addition, the location and scene can be created through computer graphics, so the virtual model is not limited in time and space, and unlike real people. The other advantage is that period in which the model can be active is very long or eternal because the virtual human doesn’t get sick or grow old.

Sourced from allkpop

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Google’s AI division shocks world with claim it’s now just 5 years away from deciphering Geordie

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Sourced from News Thump

Experts in artificial intelligence have responded with amazement, and some scepticism, to Google Brain’s recent assertion that before the decade is up, it will have cracked the linguistic Holy Grail of understanding what the residents of Newcastle are talking about.

Professor Simone Williams, a neurolinguistics expert working for the project, was adamant the prospect of being able to translate Geordie into English was no longer a pipe dream.

She went on, “After we bought AlphaGo we hooked it up to looped episodes of Geordie Shore. It went dark and after two full years, we were about to give up. But six months ago it finally made a breakthrough and conclusively proved that ‘scran’ was a phoneme used to denote a condition of hunger.”

Professor Williams admitted the project was always seen as a moonshot, particularly by financial backers.

“A lot of people didn’t believe in it. We had to go against decades of conventional thinking that Geordie wasn’t technically ‘speech’ but a method of echolocation gone horribly wrong due to alcohol abuse. And we were constantly being told there was no commercial value in knowing what a ‘canny broon’ is.

“But for linguists like myself, Geordie is the last great frontier. Once we crack it, the prospect of a sci-fi universal translator becomes very real.”

Professor Williams did say it would be at least three years before simple messages like texts could be fully translated and another two years to reach a B2 CEF level.

Until then, trade with Geordies would still have to rely on basic object recognition or getting surly residents of Gateshead to act as interpreters by pretending to agree with their ridiculous claim that they’re not a suburb of Newcastle.

Sourced from News Thump

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From Insta captions to blog posts, AI is now crunching copy for brands

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By Ryan Barwick

Chris Lu, cofounder and chief technology officer of Copy.ai, told us these tools give copywriters a “first draft” to work with.

“Marketing Brew is the home of provocative ideas, fresh thinking, provocative insights, and interesting perspectives on what they think about marketing, media and advertising. This publication gives you a way to digest their news, quick takes and new offerings in the field.”

This description of our newsletter was written by artificial intelligence. Pretty close, right?

Given only our name and a brief description—“a newsletter about marketing, media and advertising”—a tool called Copy.ai was able to spit out that paragraph.

The tool is part of a wave of smart content-churning machines that use the power of artificial intelligence to steal writing jobs make life easier for whomever’s crunching copy.

HAL meets Stan Freberg

Copy.ai and other AI-enabled copywriting companies like Jarvis and Copysmith are built upon OpenAI’s GPT-3.

According to the smart folks over at Emerging Tech Brew, GPT-3 is kind of a big deal. Trained on roughly a trillion words to predict—but not understand—text, it’s widely considered to be among the most advanced language models in existence.

“Large language models are powerful machine learning algorithms with one key job description: identifying large-scale patterns in text. The models use those patterns to ‘parrot’ human-like language. And they quietly underpin services like Google Search—used by billions of people worldwide—and predictive text software, such as Grammarly,” writes Emerging Tech Brew’s Hayden Field.

Of course, if you’re a marketer, who cares? You just need content. And lots of it. That’s where these tools come in handy. They can help write everything from Instagram captions to product descriptions to blog posts.

“We want to humanize AI. We want to help you start from something, and not a blank slate,” Copysmith CEO Shegun Otulana told Marketing Brew.

There’s an assumption that machines could take jobs away from writers, but Otulana doesn’t see it quite that way. “There’s an aspect of writing that isn’t easily replaced. A computer can’t tap into the human interactions you express in a story, the emotional aspects of a story you tease out. A computer can’t live the life of a human.”

But if you’re a writer who specializes in, say, product descriptions for e-commerce sites—or other types of copy that aren’t exactly trying to forge a human connection—these tools might pose more of a threat, he said.

For copywriters who need to bang out posts on multiple platforms like Instagram, Facebook, and LinkedIn, there’s a volume benefit to these tools, since the AI provides various options for each post. Sure, you might not actually need dozens of call-to-action phrases, but any professional could whittle those down to five good ones and tweak them if needed.

“We try to give you the first draft,” Chris Lu, cofounder and chief technology officer of Copy.ai, told us. “Content creation is a treadmill. You’ve got to make a lot of it, it has to be relevant, and it has to be on brand.”

Andrew Race, a strategist at the digital agency Juice, called Copy.ai a time saver. “In five minutes, I’ve got 25 different variations [of a headline]. Before, I would have had to write every single headline or idea out myself,” he said. He estimates it cuts his actual copywriting time in half.

  • So far Copy.ai, which debuted in October 2020, has 4,100 paying subscribers made up mostly of marketers.

Ryan’s artificial copy

We asked Copy.ai to make a couple of Facebook headlines and posts for a made-up brand called Ryan’s Lemonade, giving only the keywords “lemonade, sweet, tart, fresh.”

Here are three versions it came up with:

  • It’s So Good You’ll Want Seconds: With a history of providing quality fruit drinks, Ryan’s continues on with their new line of lemonades. From sweet and tart to a hint of fresh, Ryan’s is bound to quench any thirst.
  • Cool, Refreshing: Pure and natural lemonade sweetened only with real sugar, not high fructose corn syrup.
  • Nothing is as refreshing as Ryan’s: Have you ever felt like you were in paradise? Everyday life is a bit harder than we wish it to be. Lemon Ryan’s is the perfect amount of all things good, made by real people in the sun-drenched hills of California. $5 for a gallon? No… lets make that two!

As you can see, it isn’t perfect. But it’s pretty good, and each took less than 10 seconds. Copy.ai assumes a lot—we’re not sure where “$5” or “California” came from. “These are natural language models. All it’s trying to do is write text. It’s just trying to predict the next word,” Lu told us.

If only a few keywords are plugged in, the content produced by these tools can have a generic feel to it. Lu said he doesn’t expect plagiarism to be an issue, but did say the company is planning on adding a plagiarism detector. “The AI helps with how to say, not what to say,” he added.

Copywriter –> AI editor

Similar to Copy.ai, Jarvis also lists templates for platforms like Facebook and LinkedIn, but its bread and butter is longer-form content, like a blog post.

According to Dave Rogenmoser, founder of Jarvis, it has nearly 30,000 paying subscribers. At least 60–70% of its clients, which include Airbnb, Zillow, and CVS, are using it for projects “around 500 words,” Rogenmoser told Marketing Brew.

By inputting a few key words, Jarvis can spit out entire paragraphs, turning your average copywriter into an editor, who can guide the machine in a specific direction. If it veers off and becomes illegible, a user has to delete what isn’t working and try again. It doesn’t eliminate work entirely, as someone still has to pick and choose what works.

  • This post by Danny Veiga, a digital marketer in San Antonio, was written by Jarvis. Veiga told Marketing Brew Jarvis did about 80% of the work. The other 20% was mostly fact checking.
  • Veiga uses Jarvis for his email marketing, social posts, and homepage copy.

“Jarvis thrives when you need to write a lot of words, but they don’t need to be the most important words you’ve ever written,” said Rogenmoser. In other words, AI probably won’t win a Pulitzer anytime soon, but if you’re cranking out copy, it’ll give you a template for a flood of usable jumping points.

“It takes the mental load off. Writers are safe,” said Rogenmoser. For now.

By Ryan Barwick

Sourced from Morning Brew

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7 Tips to Use AI to Acquire and Retain Customers

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Artificial Intelligence (AI) mimics the cognitive functions of the human mind, particularly in learning and problem-solving. Many of the apps that we use today are powered by AI. From voice-activated virtual assistants to e-commerce, AI applications are everywhere.

With the advancements in AI technology and access to big data, companies across different industries are integrating AI into their processes to find solutions to complex business problems.

The application of AI is most noticeable within the retail and e-commerce space. Websites and apps can interact intelligently with customers, creating a personalized approach that enhances the customer experience.

No matter what industry your business operates in, these seven tips can help you acquire and retain customers more efficiently at a fraction of the time it takes to do things manually.

How to Use AI to Get and Keep Customers

1. Identify Gaps in Your Content Marketing Strategy

If you’re just starting with content marketing, you’ll need to know what type of content to create.

By using AI, you can identify the gaps, find fixes, and evaluate the performance of your content marketing campaign.

Take Packlane, a company that specializes in custom package designs, for example. They came up with high-quality content like helpful blog posts that provide valuable information. At the same time, the content they publish makes it easier for their target market to understand their brand and services.

If you’re in the retail or e-commerce space, you can use AI to identify the gaps in your content marketing. Your content may be focused on your products and their features, but through AI, you can determine the relevant content that addresses your audience’s needs and pain points.

2. Pre-Qualify Prospects and Leads

Not every visitor to your site will become a paying customer. If you’re not getting sales despite the massive traffic, it means you’re generating low-quality leads.

Some reasons why this happens includes:

  • Targeting the wrong audience
  • Poor content marketing strategy
  • Using the wrong type of signup form
  • Promoting in the wrong social media platforms
  • Ineffective calls to action

These explain why 80% of new leads never convert into sales. The mistakes can be rectified with the help of artificial intelligence.

AI tools can extract relevant data to help you learn more about your target audience. These tools also provide predictive analytics on your customers’ behaviour. They, in turn, help improve your lead generation strategy because you’ll know which leads to pursue, where to find them, and how to effectively engage them.

3. Provide Personal Recommendations

According to a report by the Harvard Business Review, even though there are privacy concerns when consumers’ personal information changes hands, people still value personalized marketing experiences.

Brands that tailor their recommendations based on consumer data boost their sales by 10% over brands that don’t.

Recommendation systems’ algorithms typically rely on data on browsing history, pages visited, and previous purchases. But AI is so advanced that it can analyse customers’ interactions with the site content and find relevant products that will interest the individual customer. This way, AI makes it easier to target potential customers and effectively puts the best products in front of the site visitors.

Because of AI, recommendation engines are able to filter and customize the product recommendations based on each customer’s preferences. It’s a cycle of collecting, storing, analysing, and filtering the available data until it matches the customers’ preferences.

This is an effective way of acquiring and retaining customers because there’s an element of personalization.

4. Reduce Cart Abandonment

A high cart abandonment rate is the bane of e-commerce business owners. According to a study by the Baymard Institute, online shopping cart abandonment rate is close to 70%.

Users abandon their online carts for various reasons:

  • high extra costs
  • complicated checkout process
  • privacy concerns
  • not enough payment methods, or
  • they’re not ready to buy yet.

Using AI-powered chatbots is one way to reduce cart abandonment. AI chatbots can guide the customers through their shopping journey.

AI chatbots can have a conversational approach and give the customer a nudge to prompt them to complete the purchase. These chatbots can also act as a virtual shopping assistant or concierge that can let a customer know about an on-the-spot discount, a time-sensitive deal, a free shipping coupon, or any other incentives that will encourage them to complete the checkout.

With AI, lost orders due to cart abandonment are recoverable and can lead to an increase in conversion rate for e-commerce businesses.

5. Increase Repurchases With Predictive Analytics

Predictive analytics is the process of making predictions based on historical data using data mining, statistical modelling, artificial intelligence, machine learning, and other techniques. It can generate insights, forecast trends, and predict behaviours based on past and current data.

In marketing, predictive analytics can be used to predict customers’ propensity to repurchase products as well as its frequency. When used to optimize marketing campaigns, AI-powered predictive analytics can generate customer response, increase repurchase, and promote cross-selling of relevant products.

It’s all part of the hyper personalized marketing approach, where brands interact and engage with customers and improve their experience by anticipating their needs and exceeding their expectations.

With predictive analytics, you can focus your marketing resources on customer retention and targeting a highly motivated segment of your market that are more than happy to return and repurchase your products. This approach is less expensive than advertising or implementing pay-per-click campaigns.

6. Improve Your Website User Experience

Every business—big or small—knows the importance of having a website, where visitors can interact with the brand, respond to a call to action, or purchase products. But it’s not enough to just have an online presence; it’s important that visitors to the site have a great experience while navigating through your site.

What makes for a great user experience? Users have different expectations. Some of them want faster loading time, while others want a simple and intuitive interface. But most important of all, they want to find what they’re looking for. It could be a product, content, or a solution to a problem. Whatever they may be, it’s up to you to meet their expectations.

With artificial intelligence, you can improve your website user experience tenfold. Here are some of the ways AI can be used to improve user experience.

Search relevance

This pertains to how accurate the search results are in relation to the search query.  The more relevant the results are, the better search experience the users will have. This means they are likely to find relevant content answering their queries or finding products that solve their problems.

Personalized recommendations

Content that is tailor-made for the user tends to have greater engagement which increases the likelihood of conversation. Amazon has perfected the product recommendation system using advanced AI and machine learning. AI gets data from customers and uses it to gain insights and apply predictive analysis to recommend relevant products for cross-selling opportunities.

AI chatbots

The presence of chatbots contributes to a great user experience because they provide 24/7 assistance and support in the absence of human customer service.  Users can get accurate answers to their inquiries quickly and efficiently, compared to scrolling through a text-based FAQs.

7. Social Listening for Potential Customers

Social listening is the process of analysing the conversations, trends, and buzz surrounding your brand across different social media platforms. It’s the next step to monitoring and tracking the social media mentions of your brand and products, hashtags, industry trends, as well as your competitors.

Social listening analyses what’s behind the metrics and the numbers. It determines the social media sentiment about your brand and everything that relates to it. It helps you understand how people feel about your brand. All the data and information you get through social listening can be used to guide you in your strategy to gain new customers.

Social media monitoring and listening can be done much more efficiently with the help of artificial intelligence. It’s an enormous task for a team of human beings to monitor and analyse data, but with AI-powered social media tools, all the tedious tasks can be automated. They can be trained to leverage data to provide valuable insights about your brand with high accuracy.

With AI and machine learning, your social listening can easily determine your audience, brand sentiments, shopping behaviour, and other important insights. By having this information within reach, you’ll know how you can connect with them more effectively and turn them from prospects to paying customers.

Key Takeaways/Conclusion

More companies across different industries are using the power of artificial intelligence and machine learning to significantly increase brand awareness, enhance customer engagement, improve user experience, and meet customer expectations.

  • AI can identify gaps in your content marketing strategy so that you can create content that’s relevant to your target audience.
  • AI can help you generate high-quality leads that are likely to buy your products.
  • With AI, you can personalize and tailor-fit your product recommendations based on your customers’ preferences, increasing repeat purchases.
  • AI can be integrated into your e-commerce site to reduce shopping cart abandonment.
  • AI significantly improves website user experience by making it intuitive, accessible, and easy to navigate.
  • AI-powered social media tools can help you monitor and gain valuable insights about your brand. You can then use this to develop a social media marketing strategy to gain new customers.

Achieve these milestones, and you’ll be sure to acquire new customers and retain existing ones.

Feature Image Credit: iStock/monsitj

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10 Things Your Artificial Intelligence Initiative Needs to Succeed

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By Lisa Morgan

In the race to implement AI, some companies may overlook important details that can mean the difference between success and failure.

The rush is on to implement in a battle for competitive advantage. However, in the haste to implement, some organizations are stumbling because their initiative lacks a solid foundation.

“People want to solve problems with AI just because it’s AI and not because it’s the best solution,” said Scott Zoldi, chief analytics officer at analytics decisioning platform provider FICO. “It has to be soup to nuts. How are we going to develop AI from a governed perspective of having a governance process that talks about the data, the success criteria and the risks from both a project perspective and an ethical perspective?”

Some AI initiatives falter because the thinking that went into them was inadequate. For example:

  • The AI initiative is created separately from the business strategy so it fails to make a strategic impact.
  • The success criteria are overly broad because they fail to include a success metric (E.g., “We want to be more competitive” as opposed to “We want to reduce fraud by 15% while reducing the number of false positives by 30%.”)
  • The change management aspect wasn’t considered so the initiative faces resistance.

“Shared capabilities or shared data across business units is becoming more important than the autonomy of individual units,” said Marco Iansiti, David Sarnoff professor of business administration at Harvard Business School, who heads the technology and operations management unit and chairs the Digital Initiative. “This causes all kinds of difficulties in traditional organizations because all of a sudden, you have a person who runs investment banking that has never shared anything with the person who runs wealth management. And all of a sudden, they are both interested in leveraging some of the same algorithms and some of the same components. They have to standardize because before they didn’t have to.”

The use of AI has become such a strategic issue that CEOs are getting involved in defining what their company’s AI strategy would look like.

“Earlier, we were seeing it was the CIO, CTO and some CXOs, but now the leading CEOs realize that this is going to redefine the future of their industry and the future of their own company,” said Arnab Chakraborty, global managing director, applied intelligence North America lead at global consulting company Accenture. “They’re looking at this as a reinvention of their business in the context of where things are headed with AI.”

Some of the common missteps can be avoided or minimized by thinking through the initiative in a holistic manner and involving those in the value stream who can help think through the various aspects — opportunities, risks, potential impacts, success factors, data requirements, compliance issues, governance, etc. Other success factors follow.

Feature Image Credit: Gorodenkoff via Adobe Stock

By Lisa Morgan

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include … View Full Bio

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NFTs and AI Are Unsettling the Very Concept of History

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By Rick Prelinger

Non-fungible tokens and artificial intelligence make tracing the origins of a digital object more fragile. What are the world’s archivists to do?

As an archivist, I’m excited about what disruptive innovations like non-fungible tokens (NFTs) and artificial intelligence may mean for archives. But I’m also worried. These developments pose existential threats to our field, and by extension, to the survival of human history and culture.

I give old films away for free. It started in 1999 when I was seduced by the promise, excitement, and just-felt-rightness of the gift economy. Not 30 seconds after we first met, Internet Archive founder Brewster Kahle asked me, “Want to put your film archives online for free?” Braving the new world of video digitizing and sputtery streaming changed my life. Our archival footage enabled thousands, maybe millions of artists, video makers, educators, and even post-Communist Polish village kids to remix history and bring the past into the present. I never knew how many people were using our material or who they were—but wasn’t that the point?

In 1999 the future of our archives was to be consumed, to enrich public memory with new evidence without hassle. I wanted our archives to be as ubiquitous as infrastructure, to work their way into every corner of the net, to propagate everywhere without need for attribution or credit. I wanted our archives to vanish in the web.

I still do.

But now the survival of archives as we know them is uncertain. Whether we know it or not, we all rely on a patchwork of chronically underfunded public and private institutions that hold the world’s histories and cultural heritages in trust for all of us and make them accessible. Every time we see an old photo, hear a historical recording, see a news clip, or find a family history document, it likely originated in an archive. While we see and touch massive digital archives online, most archives are still largely undigitized collections of physical media like film, video, music, photographs, and paper documents. By design, archives are deliberate and thoughtful, with a timeline designed to preserve culture “forever.” They’re not built to nimbly weather disruption.

It was only a matter of time before the market figured out a way to manufacture and sell digital scarcity, and the marketplace for cultural objects has moved well past the archival ecosystem. Artists, gamers, entertainers, athletes, and executives now sell NFTs, tokenized digital objects whose authenticity is said to be assured by the reverse traceability of blockchain transactions. The combination of Covid-19 isolation and cryptocurrency profits created a powerful incentive for digital-positive collectors to compete for these NFTs, and some creators are raking in Ethereum.

Law professor Tonya M. Evans optimistically suggests that crypto art offers Black artists and communities opportunities to bypass white art gatekeepers and “capture and own the value of the culture that they produce.” While the current boom may well go the way of the 1920s Florida land-rush hype, NFTs are the first step in what’s likely to be a robust market for unique or scarce digital objects. Many of these digital objects won’t be born-digital; instead they’ll be one-off digitized copies of physical materials, for which there could be a huge market. Who wouldn’t want to own the master digital copy of their favourite author’s journal, a photograph of Abraham Lincoln or Frederick Douglass, or the recently rediscovered newsreel of the 1919 Black Sox scandal?

Nothing could be a greater cultural and ethical shock to archives than NFTs. Prevailing archival ethics generally dictate that all users are treated equally, and that archival materials aren’t exposed or sold only to high bidders. And once archives select materials for retention, they consider themselves in most cases ethically bound to do so permanently.

If an archive has a merch business, it’s tiny: keychains and postcards. As poor a fit with archival DNA as tokenizing archive collections as NFTs may be, the possibility of leveraging digital scarcity by selling NFTs while retaining physical materials is a hefty temptation. The archival world is a world of inadequate budgets and financial constraint, filled with underpaid workers and massive, poorly resourced projects like digital preservation, and the challenging task of digitizing analog materials. Will archives be tempted by the potential upside of NFTs and tokenize digital representations of their crown jewels (or the rights to these assets)? This would worsen an already bad situation, where institutions like our Library of Congress hold physical copies of millions of films, TV programs, and recordings that can’t be touched because someone else holds the copyright. Ideally, archives and museums should own and control both the physical and digital states of its collections. That won’t happen if they have to sell or license NFTs in order to survive. And there’s another risk: Minting NFTs requires a lot of energy (though we may hope for a cleaner process), and the future security of archives is threatened by climate change. Researchers have discovered that almost all archives will be affected by risk factors like sea level rise, increased temperature, or heavy rainfall.

For those working with the raw materials of history, integrity and authenticity are the chief necessities. How do NFTs address these? While the blockchain is supposed to draw an unbroken link between creator/tokenizer and purchaser, it’s just a record of transactions that might be tainted or even bogus. We know the original Mona Lisa resides in the Louvre, but it’s very hard to identify who really created and who owns many of the millions of creative works made in the analog era. It’s nearly impossible to track who owns the even greater number of digital works made every year. So while the blockchain can help us follow sales and transfers of digital objects, how do we know the original representations made about these objects can be trusted? Already there are many NFTs on offer that are nothing more than tokenized versions of works belonging to third parties, often scraped from museum websites. This isn’t a new problem—after we put digitized films from our archives online for free, many other stock footage companies downloaded them and sold them as their own. Who will be the arbiter of which copies are closest to the original? The quagmire recalls Philip K. Dick’s The Man in the High Castle, where American craftspeople build near-perfect counterfeits of American cultural collectibles. Authenticity is based on aura, aura on belief. If many Alices sell tokenized, pirated copies of the Zapruder film to many Bobs, this bombs the blockchain with many transactions that obfuscate the fact that these might be pirated versions. The solution, obviously, is to know your source—to authenticate objects and their provenance by authenticating their owners. But can that scale in a marketplace where transactions might number in the billions?

Registries are emerging to authenticate sources and provenance, and perhaps even indemnify purchasers against false representations by sellers. These have long existed in the collectibles business. Rare coins are frequently processed by trusted grading and authentication services, which charge to inspect coins and then encapsulate them in sealed plastic slabs. While I can see this happening for the four existing colour versions of Edvard Munch’s The Scream, how would it work for millions of new digital works? Will these registries be proprietary or open, and how much will their services cost? And authentication systems ultimately rest on the accuracy of information they receive. Who would arbitrate conflicting claims between potentially millions of squatting bots feuding over provenance and authenticity issues? And could such registries be flooded with blockchain-authenticated look-alikes and deepfakes? If you think this is improbable, just look at YouTube, where Content ID, its suite of pattern-matching algorithms that’s claimed 800 million videos since its launch, supposedly enforces the rights of copyright owners by flagging unauthorized uploads. The system generates huge numbers of false positives and won’t authorize legitimate fair uses of content. And copyright to millions of videos (including many public domain works) is claimed by squatters. Fuzziness and a high error rate may be OK for a commercial service like YouTube. But it’s a disaster for cultural and historical institutions that derive income from reuse. How would a blockchain full of false transactions complicate ownership and authenticity?

One working solution is for cultural and historical institutions like archives to run their own trusted registries of digital objects. But this is expensive, and it creates further incentives for archives to monetize their holdings and become less accessible to non-commercial users, like genealogists, the group that uses archives more than anyone else. If the need to administer NFTs makes NFTs inevitable, that’s a loss. Today’s archivists are faced with the need to come to terms with NFTs without having the resources to ensure their needs are met.

NFTs make archival authenticity, and thus history, more fragile. And right now authenticity is threatened by AI.

If you’ve seen Denis Shirayev’s upscaled historical videos, you’ve seen the past enhanced by a touch of the future. He takes videos scanned from very old films, like our poignant A Trip Down Market Street Before the Fire, shot just days before the 1906 quake and fire that devastated San Francisco, upscales them to 4K, smoothes out jitter and adds colour. (Today any video editor can make something almost as good using off-the-shelf tools like Topaz Video Enhance AI.) Shirayev’s videos are beautiful and compelling, but they show you something that never was. They’re not archival; they’re fiction. Artist and author Gwen C. Katz recently demonstrated the flaws of AI colorization, showing that software substitutes a drab colour palette for the brilliant colours of historical reality, and pointing out that only primary historical evidence unaffected by our preconceptions can present a plausible image of the past. Will prettified AI-enhanced digital objects made to draw in the eyeballs of distracted web surfers push the original, less attractive evidence out of view? Will people modify archival materials in such a way as to marginalize their original source? Will established archives sit by as others embellish their collections into prettier, more marketable objects? And, worst of all, will pretty images stand in for the inconvenient, hard-to-view authentic record?

The question of “real” vs. “pretty” recently exploded when a Vice article (now removed) revealed Matt Loughrey‘s colorization and alteration of mug shots taken in a Khmer Rouge torture center just before their subjects were murdered. Cambodian genocide survivors led a protest against Loughrey’s project, which added smiles to a few victims’ faces, and the Tuol Sleng Genocide Museum and the Government of Cambodia called for his apology and for the photographs to be taken down. From the viewpoint of historical and archival authenticity, Loughrey’s call for infusing archival photos with a sense of contemporary realism was perhaps most disturbing. “The image that we’ve come to accept as standard is becoming obsolete owing to the advance in display technology,” he told the Daily Mail. “When we consider a museum or a library or a documentary, as these displays advance, which they are rapidly, the producers of these are going to be less inclined to display and use these images. They’re going to have to find new images by repurposing them.” The actual archival record, in other words, can no longer stand by itself.

Together these two developments pose an existential threat to archives. Archives won’t go under, but it’s going to take serious thinking, significant new funding, and public education to help these under-resourced, deliberate organizations respond to rapid change. The integrity and survival of these important institutions are in everyone’s interest. Archives aren’t perfect, but they can help keep us honest. They’re a force for historical accuracy and accountability, if we trust the records in their collections and know their provenance. All of us should hope the promise of NFTs and AI won’t slide us into a world of “fake archives” and speculation in archival collectibles.

I still want our film archives to be consumed freely by makers in familiar media and in media we haven’t yet begun to imagine. I still want our archives to vanish in the web. But I don’t want history and the institutions that painstakingly preserve it to disappear into an eternal and amnesic present.

Featured Image Credit: Sam Whitney; Getty Images

By Rick Prelinger

Rick Prelinger is an archivist, filmmaker, writer, and educator whose collection of 60,000 films was acquired by the Library of Congress in 2002. He is currently chair and professor of film and digital media at the University of California, Santa Cruz.

Sourced from WIRED

 

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Adobe puts artificial intelligence tools into its marketing software

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Reporting by Stephen Nellis in San Francisco; Editing by Marguerita Choy

(Reuters) – Adobe Inc ADBE.O said on Monday that it has put a new set of artificial intelligence tools into its digital marketing software with the aim of helping companies sharpen their marketing campaigns.

Once known for applications like Photoshop, Adobe has become one of the biggest providers of software for running such campaigns, which businesses use to decide which of thousands of images and pieces of written to content to show to potential customers. Growth in its marketing software division has helped send shares up nearly 50% this year.

The artificial intelligence features released on Monday aid that effort by, for example, scanning and labelling thousand of product images by colour and shape, or using natural-language processing technology to read an article to determine its subject.

That makes it easier for marketing campaigns to make a recommendation, whether that means showing a person browsing an e-commerce site a pair of shoes similar to ones they have previously viewed or a news website suggesting a story on a similar subject to the one just read.

Such artificial intelligence technology has existed for several years, but using it generally required corporate marketing departments to export data from their systems and work with another division of the business to use, slowing the work down, Ali Bohra, director of strategy and product marketing for intelligence services at Adobe, said in an interview. Adobe has placed the technologies directly inside the marketing systems, reducing the need to export data.

“When you’re thinking about the need to be agile and work in real time, this is not a process that works very well,” Bohra said.

Feature Image Credit: An Adobe Systems Inc software box is seen in Los Angeles, California, U.S., March 13, 2017. REUTERS/Lucy Nicholson

Reporting by Stephen Nellis in San Francisco; Editing by Marguerita Choy

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China and AI: what the world can learn and what it should be wary of

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China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars.

The move has led – at least in the West – to warnings of a global AI arms race and concerns about the growing reach of China’s authoritarian surveillance state. But treating China as a “villain” in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government’s approach to AI that are highly concerning and rightly should be condemned, it’s important that this does not cloud all analysis of China’s AI innovation.

The world needs to engage seriously with China’s AI development and take a closer look at what’s really going on. The story is complex and it’s important to highlight where China is making promising advances in useful AI applications and to challenge common misconceptions, as well as to caution against problematic uses.

Nesta has explored the broad spectrum of AI activity in China – the good, the bad and the unexpected.

The good

China’s approach to AI development and implementation is fast-paced and pragmatic, oriented towards finding applications which can help solve real-world problems. Rapid progress is being made in the field of healthcare, for example, as China grapples with providing easy access to affordable and high-quality services for its ageing population.

Applications include “AI doctor” chatbots, which help to connect communities in remote areas with experienced consultants via telemedicine; machine learning to speed up pharmaceutical research; and the use of deep learning for medical image processing, which can help with the early detection of cancer and other diseases.

Since the outbreak of COVID-19, medical AI applications have surged as Chinese researchers and tech companies have rushed to try and combat the virus by speeding up screening, diagnosis and new drug development. AI tools used in Wuhan, China, to tackle COVID-19 – by helping accelerate CT scan diagnosis – are now being used in Italy and have been also offered to the NHS in the UK.

The bad

But there are also elements of China’s use of AI which are seriously concerning. Positive advances in practical AI applications which are benefiting citizens and society don’t detract from the fact that China’s authoritarian government is also using AI and citizens’ data in ways that violate privacy and civil liberties.

Most disturbingly, reports and leaked documents have revealed the government’s use of facial recognition technologies to enable the surveillance and detention of Muslim ethnic minorities in China’s Xinjiang province.

The emergence of opaque social governance systems which lack accountability mechanisms are also a cause for concern.

In Shanghai’s “smart court” system, for example, AI-generated assessments are used to help with sentencing decisions. But it is difficult for defendants to assess the tool’s potential biases, the quality of the data and the soundness of the algorithm, making it hard for them to challenge the decisions made.

China’s experience reminds us of the need for transparency and accountability when it comes to AI in public services. Systems must be designed and implemented in ways that are inclusive and protect citizens’ digital rights.

The unexpected

Commentators have often interpreted the State Council’s 2017 Artificial Intelligence Development Plan as an indication that China’s AI mobilisation is a top-down, centrally planned strategy.

But a closer look at the dynamics of China’s AI development reveals the importance of local government in implementing innovation policy. Municipal and provincial governments across China are establishing cross-sector partnerships with research institutions and tech companies to create local AI innovation ecosystems and drive rapid research and development.

Beyond the thriving major cities of Beijing, Shanghai and Shenzhen, efforts to develop successful innovation hubs are also underway in other regions. A promising example is the city of Hangzhou, in Zhejiang Province, which has established an “AI Town”, clustering together the tech company Alibaba, Zhejiang University and local businesses to work collaboratively on AI development. China’s local ecosystem approach could offer interesting insights to policymakers in the UK aiming to boost research and innovation outside the capital and tackle longstanding regional economic imbalances.

China’s accelerating AI innovation deserves the world’s full attention, but it is unhelpful to reduce all the many developments into a simplistic narrative about China as a threat or a villain. Observers outside China need to engage seriously with the debate and make more of an effort to understand – and learn from – the nuances of what’s really happening.

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