Technology
How AI technology is changing consumer habits
With ChatGPT taking the internet by storm, technology is front of mind for both consumers and brands. Consumers are excited about new developments in the virtual space, and are eager to test AI tools and products out themselves, while brands are seeking ways to apply new Artificial intelligence (AI) tech in order to grow their businesses. In this blog we explore how AI technology is changing consumer search habits online, and what impact it will have on consumer behaviour.
Brands need to adapt as Generation Z shifts search behaviour to social media
While search engines may continue to dominate, the younger generations are increasingly making use of alternative ways to search for information. This is most evident when it comes to clothes, as nearly half of Gen Z are most likely to turn to social media when searching for outfit ideas, while one in three would turn first to social media for gift ideas.
One advantage of using social media sites such as TikTok for search is its ability to provide video content, with personal recommendations, rather than just links to websites. The video-based responses provided by platforms, such as TikTok and Instagram, can offer a more immersive and engaging response than search engines. It can also offer more ‘personal’ recommendations by others who have uploaded reviews and content. In the context of fashion, vibrant tryout videos will be of more appeal to people who are looking to see how different fashion items fit together, or not, hence providing more useful information for the consumer instead of the usual bland, static images.
TikTok has recognised its users wanting to use the site in this way and is seeking to monetise it. For example, the platform has been testing features that identify keywords in comments and links to search results for them. Although the platform has recently become embroiled in controversy in the US, its business model and formula is likely to be ingrained in Gen Z creators, advertisers and audience, and consumers are getting more used to finding advertising content that engages them and speaks to their needs.
Search engines fight back with AI enhancements
As social media platforms gain increasing popularity as de facto search engines, the old guard are fighting back, with AI rapidly improving search results in search engines. With the explosion of ChatGPT, conversational AI could take this even further, with both Bing and Google exploring how the technology can provide a more personalised and nuanced search result than simply offering a list of hyperlinks to relevant websites. Improvements in natural language processing (NLP) models will enhance performance in voice searches, thus also enhancing the accessibility of internet usage.
Tech giant Google has been seeking ways to make search more ‘immersive’. Using AI, the search engine can now recommend specific parts of a video that could be relevant to a search. Google Maps already features an augmented reality version that uses the camera of a phone to overlay search information on an image of the surrounding area.
Google is implementing new AI technologies in its suite of services, including new AR functions in its signature search engine. Source: Google
Microsoft, on the other hand, is integrating OpenAI into its Edge browser and new Bing search engine with features similar to ChatGPT. Features include a Bing Chat function which transforms search data into a full interactive human-like conversation. This new launch by Microsoft could encourage some consumers to the browser and alter the search market share.
AI poses challenges, but brands and consumers will benefit in the long run
AI has already improved and transformed the search experience behind the scenes, but the introduction of more conversational text based answers could herald a new era of search. The idea of AI and having ‘conversations’ with computers can divide consumers. While some think it’s exciting as AI could make life easier, others worry about the reliability of the information, and what happens when AI content becomes so widespread online, that AI search engines are generating answers based on AI generated content.
For brands, the integration of AI will provide an opportunity to create a new and exciting way to engage with consumers. For example, brands may need to rethink how they create an online presence so that Generative AI search talks favourably about them, or recommends them in the right instances. However, Generative AI will also create significant opportunities for the experience within a brand’s site. For example, Shopify has announced plans to add a new search function to its app in 2023, leveraging ChatGPT’s technology.
OpenAI announced that ChatGPT and Whisper models are now available on their API, giving developers access to cutting-edge language and speech-to-text capabilities; Shopify is one of the brands that uses this AI-technology extensively to help consumers find the right products. Source: OpenAI
What we think
Advances in AI technology will continue to influence consumers and brands as they seek to harness the power of the internet and social media. The integration of conversational AI into search engines will transform the way consumers look for information and discover brands and products. As search becomes more immersive and conversational it will change the way brands need to position themselves online to ensure they remain visible and stand out from the myriad of content.
Brands need to be aware that the way consumers search for information is changing. Search engine optimisation is just one aspect of an increasingly fragmented online journey. Social media activity shouldn’t just be viewed as a way to drive traffic to a website or generate buzz around a brand, but it should be viewed as an opportunity to help consumers find what they are looking for and even buy directly via the platform.
Generative AI has the potential to transform the way consumers engage with brands and search for information. Gen Z will be first to embrace this technology, and will expect a more personalised and conversational relationship with brands than ever before.
Technology
The best iPhone 16 Pro and Pro Max deals
Apple has officially launched the iPhone 16, and now you can begin to make your iPhone 16 Pro and iPhone 16 Pro Max orders. Here we’re focusing specifically on the iPhone 16 Pro and iPhone 16 Pro Max, which are housed separately in the Apple store, but we’ve also covered iPhone 16 and iPhone Plus deals. We’re going to look at how to get the best deal via Apple or other retailers’ offers. The iPhone 16 Pro and iPhone 16 Pro Max officially released starting on September 20.
We found that getting the best deal from the Apple store was not entirely straightforward. Follow along with our guide for your best price.
iPhone 16 Pro and iPhone 16 Pro Max — Apple deal guide
At the top of you’ll see the basics on order deals all in one spot. At the top of the page (in the red rectangle in the image above) you’ll see a brief overview of all of the current offers. It’s worth noting, though, that there is some fine print and navigating through the store page isn’t a perfect experience. To see what we mean, tap the button below and follow along with our iPhone 16 Pro and Pro Max ordering guide, where we’ll show you exactly what to click to get the lowest price.
Apple’s iPhone 16 Pro and 16 Pro Max carrier deals — AT&T, Verizon, T-Mobile
Getting and understanding the available carrier deals from Apple’s store is the trick to getting the best preorder deal on the phones. Unfortunately, the numbers and steps to get there are somewhat confusing. By the end of this section, however, you’ll know how to get an iPhone 16 Pro for as low as $0.00/month from your favorite carrier and get the best Apple Store deal on the iPhone 16 Pro Max.
We’ll start by entering a phone into “Apple Trade In.” but ignore the price — it is wrong. When we go to get the best carrier deals, later, you’ll find that the trade in is worth more than stated. It makes planning frustrating, but at least it errs in your favor and they’re letting you get started early. Also note that Verizon makes ordering easier, as they’re offering a flat rate on any trade in phone of any condition. So, if you’re going with Verizon everything will be a little easier to navigate.
If the supplied phone meets all of the conditions to be in “good condition” go ahead and tap “Yes” for the relevant box. Note, however, that you can still trade in a phone that is missing one of the conditions to be considered “good” by Apple. Just tap “No” and follow the on-screen questionnaire to the best of your ability. With this requirement out of the way, you’re now ready to find your best rate on an iPhone 16 Pro and iPhone 16 Pro Max via AT&T, Verizon, or T-Mobile.
Once you’ve input your trade-in phone, tap “Finance” under “Payment options.” and hit the “Carrier” button. You’ll get a screen that looks something like the image above. These financed deals on the phone offer the very best rates on the phone in exchange for committing to a carrier for two or three years.
On this screen you’ll get your carrier-specific pre-order offers from Apple. In orange, at the top of each offer, you’ll see the full amount you’re getting back in bill credits from the carrier. Then, just below the bolded text you’ll see a monthly price for the phone and how many months you’ll need to be with them. Remember, you’ll need to stay with the carrier for the full duration of the term, so you’ll still be paying for service even with a great deal. Note that the amount that you can expect to get back will change depending on the version of the phone and how much storage you are after.
At this time, you’ll want to do your planning to see how much you get back on each phone, with each carrier, at each storage amount until you find something that fits your budget and needs. You can quickly change to other version of the phone (and storage sizes) by scrolling up and choosing them. However, you’ll need to remember to tap the ‘Carrier’ button again when you scroll back down to properly compare the offers. While experimenting with the page, my entered phone sometimes deleted itself when switching between the Pro and Pro Max versions, but not always. This seems to be an error happening on the iPhone 16 Pro and iPhone 16 Pro Max page only, so be sure to check if your trade-in phone is still inputted if you see an odd price increase.
So, what’s the best deal you can get this way? For AT&T, Verizon, and T-Mobile you can get $999 in trade-in credit applied to the iPhone 16 Pro 128GB storage version when we traded in a “good” iPhone 15 Pro Max. This makes it $0.00/month with your phone plan purchase. All other versions of the iPhone 16 Pro and all of the iPhone 16 Pro Max storage versions required some additional payment for the phone.
Apple’s iPhone 16 Pro and iPhone 16 Pro Max deals — Boost Mobile
Don’t have a trade in phone? No problem — if you want to go with Boost Mobile. When you finance with Boost Mobile and connect on their Boost Mobile Infinite Access Plan for 36 months, you’ll receive $1,000 in Boost Mobile credits. That means that you can get the 128GB version of the iPhone 16 Pro for $0 additional dollars per month.
This is one of the best ways to get an iPhone 16 Pro ordered on the cheap if you don’t have a phone for trade-in.
AT&T’s iPhone 16 Pro and iPhone 16 Pro Max deals
Getting your iPhone 16 Pro or 16 Pro Max from AT&T is pretty simple, all things considered. The iPhone 16 Pro is straight up free if you trade in your old phone (and it is eligible). Want the Pro Max instead? You can still save up to $1,000 from the total cost of the phone by giving up your old phone. That’ll take your monthly payment on the phone from $33.34 to $5.56 over the course of 36 months. Tap the button below to see AT&T’s full iPhone lineup and choose the offer that makes the most sense for you.
Boost Mobile’s iPhone 16 Pro and iPhone 16 Pro Max deals
If you don’t have an old phone that’s worth much or just don’t like to part with your old iPhones, you may want to take advantage of Boost Mobile’s deals. Boost Mobile’s deals do not require a trade in phone.
You’ll save $1,000 on an iPhone 16 Pro or iPhone 16 Pro Max when you sign up with Boost Mobile’s Infinite Access plan. It’s a $65/month plan that provides unlimited 5G, global roaming, and an annual iPhone upgrade (up to $830 in value). Check it out on their website by tapping the button below. You can also find and deals on Amazon.
Verizon’s iPhone 16 Pro and iPhone 16 Pro Max deals
The big flashy deal at Verizon right now is that you can get “The new iPhone 16 Pro on us” but they also have a deal on the 16 Pro Max. Here are the important details:
If you get a 128GB iPhone 16 Pro on a new or upgraded Unlimited Ultimate plan and trade in an Apple, Google, or Samsung phone (that’s been active on your account for at least 60 days), you can get $1,000 of trade-in/promo credit applied over 36 months while you’re with the service, which is enough to make the $1,000 phone free. In other words, it is “on us” (that is to say, Verizon) if you do everything else they ask for. Note that this is by fair their best preorder deal on the iPhone 16 Pro.
There are iPhone 16 Pro Max deals from Verizon as well, however, even if they aren’t as strongly advertised. In fact, you can get that same $1,000 on any Pro Max phone with an eligible trade in and a new Unlimited Ultimate plan for 36 months. However, as the iPhone 16 Pro Max phones are more expensive, you’ll still have to pay something to get your new phone. For example, the smallest 256GB storage version of the phone would be reduced to a cost of just $5.55, from $33.33, over the course of the 36 months. Considering the price of a phone plan, it isn’t a huge amount extra to pay.
To take advantage of any of these deals, tap the button below to find Verizon’s complete iPhone lineup.
T-Mobile’s iPhone 16 Pro and iPhone 16 Pro Max deals
T-Mobile’s offers for the iPhone 16 Pro and iPhone 16 Pro Max largely revolved around a trade in and having or getting one of their 5o5G plans, the best of which is 5o5G Next. 5o5G Next offers consistent phone upgrades that don’t leave existing customers paying worse prices than new customers. It also comes with bonuses like Apple TV+ and Netflix so you can enjoy using your data for good entertainment. Deals also exist for 5o5G Plus and the standard 5o5G plans, but they’re somewhat less good, especially on the Pro Max version of the phone. Here’s how it all breaks down.
Between the iPhone 16 Pro and iPhone 16 Pro Max, the absolute best deal we’re seeing from T-Mobile is on the iPhone 16 Pro, where you can get it for free if you have an eligible trade in and get it on Go5G Next. Remember, you can also switch to Go5G Next at this time to get the deal. Alternatively, you can save $830 off of the iPhone 16 Pro (bringing it from $1,000 to $170) if you trade in a phone and get a new standard Go5G line or trade in with a Go5G Plus plan.
T-Mobile’s deals on the iPhone 16 Pro Max offer the same dollar value as for the iPhone 16 Pro, but the feeling isn’t quite the same. By this, we mean that with an eligible trade in and a 5o5G Next plan you’ll get $1,000 off or you can get $830 off with either a new line and a trade in or a trade in with Go5G Plus. The big difference? The Pro Max costs more, so that $1,000 off will still make it cost $200 instead of being free. In other words, you’ll get the same value for your trade in no matter the phone you pick, but the psychological crunch factor might feel better for the iPhone 16 Pro.
Presently, T-Mobile has six promotional offers on each phone in the iPhone 16 series lineup. Tap the button below to see the ones covered here as well as what else they have to offer.
Best Buy’s iPhone 16 Pro deals
We’re seeing the iPhone 16 Pro (but, unfortunately not the Pro Max) being offered at Best Buy, with the phones either being tied to Verizon or AT&T, and you can save up to $1,000 via a trade in.
The biggest advantage of trying to trade in for an iPhone 16 Pro on Best Buy is their wide range of acceptable brands to trade in. So, if you have something that you want to trade in but it wasn’t eligible for Verizon or AT&T’s offers, go ahead and try at Best Buy. Plus, now makes a great time to use any Best Buy credits you’ve accumulated from previous deals or gotten from returns.
Technology
New Spectacles are “obviously bad,” former Snap engineer says
Recently, Snap announced a new model of Spectacles, its series of “smart glasses.” The product caused a divide in the community due to poor design and feature choices. Now, a former Snapchat engineer who worked on the latest Spectacles claims that they are “obviously bad.” He also hints at problems during development.
New Snapchat Spectacles redesign and features a “disaster,” says engineer who worked on them
Creating a good tech product requires more than just integrating all the impressive technologies available. You also need to strike a balance between functionality and practicality. The new Spectacles boast a miniature LCOS projector in a limited space, which is a technological milestone. However, they did so at the cost of multiple drawbacks, such as a clunky design, a limited 45° FOV, and a battery life of just 45 minutes.
Sterling Crispin, a former Snap Spectacles engineer, lamented about the final result. “I worked on these for about a year at Snap, and I have a million negative things to say about the experience and the device, but I think the product speaks for itself and is obviously bad,” Crispin said on X. The engineer was especially harsh on the product, even calling it a “disaster.” So, even though he worked on the project, it seems he wants to completely disassociate himself from it.
Crispin also suggests that problems arose from misdirection during development. “This device is a set of very bad decisions that compounded, making them even worse,” he said. “Everyone working on it knew the problems and who was making them.”
The Industry may not yet be ready for standalone AR glasses
That said, it seems that even the social media company is aware that the product is not suitable for the consumer market. Snap is currently offering the glasses to developers looking to enter the Snap OS AR ecosystem. Developers can access the new Spectacles through a rental model, which costs $99 per month (with a minimum one-year period). Previous models stood out for their aesthetics and capabilities of creating content to share on the app.
Smart glasses technology is advancing rapidly, and products are reaching more and more people. However, it seems that it is still too early to achieve a compelling standalone AR product with such a form factor. Recent reports say that Apple has realized this, so its first Apple Glasses will be similar to Ray-Ban Meta’s, without AR features. Current technological limitations are still an obstacle to overcome. However, Snapchat made it easy to backlash against the new Spectacles with an aesthetically bad redesign.
CHEERS TO THE NEXT ERS OF AR GLASSES WITH @Spectacles!!! pic.twitter.com/L0cKKipY2q
— Sophia Dominguez (@sophiaedm) September 17, 2024
Technology
How to Use GPT-4o Voice Mode
In this tutorial, learn how to maximize your content creation with GPT-4o Voice Mode. Discover the step-by-step process to effectively use this cutting-edge feature.
Science & Environment
Antarctica’s “Doomsday Glacier” is set to retreat “further and faster,” scientists warn
The outlook for “Doomsday Glacier” just got gloomier.
Scientists are warning the Antarctic Ice Sheet, known formally as the Thwaites Glacier, will deteriorate “further and faster” and that sea level rise triggered by the melting could impact “hundreds of millions” in coastal communities.
“Towards the end of this century, or into the next century, it is very probable that we will see a rapid increase in the amount of ice coming off of Antarctica,” said Dr. Ted Scambos, a glaciologist at the University of Colorado. “The Thwaites is pretty much doomed.”
The findings are the culmination of six years of research conducted by the International Thwaites Glacier Collaboration, a collective of more than 100 scientists.
The “Doomsday Glacier,” roughly the size of the state of Florida, is one of the largest glaciers in the world. Scientists predict that its collapse could contribute to 65 centimeters, or roughly 26 inches in sea levels to rise.
The sea level rise could be even higher though if you account for the ice the Thwaites will draw in from the large surrounding glacial basins when it collapses. “That total will be closer to three meters of sea level rise,” Scambos said.
According to the researchers, the volume of water flowing into the sea from the Thwaites and its neighboring glaciers has doubled from the 1990s to the 2010s.
Approximately 1/3 of the front of the Twaites is currently covered by a thick plate of ice — an ice shelf — floating in the ocean that blocks ice from flowing into the sea. However, Scambos said the melting is accelerating and that the ice sheet is “very near to the point of breakup.”
“Probably within the next two or three years, it will break apart into some large icebergs,” he said. This will eventually leave the front of the glacier exposed. This may not necessarily lead to a sudden acceleration in melting, but it will change how the ocean interacts with the front of the ice shelf, Scambos said.
Deep ridges that prevent ice from flowing into the ocean are on their way out. The ridges, in the bedrock below the ice sheet in Antarctica, provide a “resistive force” against the ice, Scambos said, that slows down its flow into the ocean. As the Thwaites collapses, it will lose contact with these protective ridges, causing more ice to empty into the ocean.
One of the more surprising findings to come from the International Thwaites Glacier Collaboration was how tidal activity around the glacier is pumping warmer sea water into the ice sheet at high speed. That water, which is a couple of degrees above freezing, is getting trapped in parts of the glacier and forced further upstream.
“It goes in every day, it gets squashed up under the glacier. It completely melts whatever freshwater ice it can, and then it gets ejected, and then the whole thing starts again,” said Scambos.
The new findings from the International Thwaites Glacier Collaboration add to a vast body of research on how the deterioration of glaciers worldwide could contribute to sea level rise. In May, a study found that high-pressure ocean water is seeping beneath the “Doomsday Glacier” leading to a “vigorous ice melt.”
Study co-author Christine Dow called the Thwaites the “most unstable place in the Antarctic” and said the speed at which its melting could prove “devastating for coastal communities around the world.”
Researchers at the University of California, Irvine predicted the ocean could rise by about 60 centimeters, or about 23.6 inches, roughly on par with the predictions from scientists part of the International Thwaites Glacier Collaboration.
Scientists also have also warned about the potential consequences if the Greenland ice sheet were to melt. Greenland’s melting ice mass is now the No. 1 driver of sea level rise, according to Paul Bierman, a scientist at the University of Vermont. If it melts completely, scientists project it could lead to 20 to 25 feet of sea-level rise.
Rising global temperatures linked to climate change have made oceans warmed and generated new wind patterns that make these glaciers more susceptible to melting.
“It is very likely related to increasing greenhouse gasses in the atmosphere, which changed wind patterns around Antarctica, and therefore changed ocean circulation around Antarctica,” said Scambos. “That’s the main culprit.”
Scientists project that without intervention, the Thwaites could completely disappear by the 23rd century.
Technology
Exploding interest in GenAI makes AI governance a necessity
Enterprises need to heed a warning: Ignore AI governance at your own risk.
AI governance is essentially a set of policies and standards designed to mitigate the risks associated with using AI — including generative AI — to inform business decisions and automate processes previously carried out by human beings.
The reason it’s now needed, that it cannot be ignored, is that enterprise interest in generative AI is exploding, which has led to more interest in traditional AI as well.
Historically, AI and machine learning models and applications were developed by and used mostly by small data science teams and other experts within organizations, never leaving their narrow purview. The tools were used to do forecasting, scenario planning and other types of predictive analytics, as well as automate certain repetitive processes also overseen by small groups of experts.
Now, however, sparked by OpenAI’s November 2022 launch of ChatGPT, which represented significant improvement in large language model capabilities, enterprises want to extend their use of AI tools to more employees to drive more rapid growth. LLMs such as ChatGPT and Google Gemini enable true natural language processing that was previously impossible.
When combined with an enterprise’s data, true NLP lets any employee with an internet connection and the requisite clearance query and analyze data in ways that previously required expert knowledge, including coding skills and data literacy training. In addition, when applied to enterprise data, generative AI technology can be trained to relieve experts of repetitive tasks, including coding, documentation and even data pipeline development, thus making developers and data scientists more efficient.
That combination of enabling more employees to make data-driven decisions and improving the efficiency of experts can result in significant growth.
If done properly.
If not, enterprises risk serious consequences, including decisions based on bad AI outputs, data leaks, legal noncompliance, customer dissatisfaction and lack of accountability, all of which could lead to financial losses.
Therefore, as interest in expanding the use of both generative AI and traditional AI transitions to more actual use of AI, and as more employees with less expertise get access to data and AI tools, enterprises need to ensure their AI tools are governed.
Some organizations have heeded the warning, according to Kevin Petrie, an analyst at BARC U.S.
“It is increasing,” he said. “Security and governance are among the top concerns related to AI — especially GenAI — so the demand for AI governance continues to rise.”
However, according to a survey Petrie conducted in 2023, only 25% of respondents said their organization has the proper AI governance controls to support AI and machine learning initiatives, while nearly half said their organization lacks the proper governance controls.
Diby Malakar, vice president of product management at data catalog specialist Alation, similarly said he has noticed a growing emphasis on AI governance.
SingleStore customers, like those of most data management and analytics vendors, have expressed interest in developing and deploying generative AI-driven tools. And as they build and implement conversational assistants, code translation tools and automated processes, they are concerned with ensuring proper use of the tools.
“In every customer call, they are saying they’re doing more with GenAI, or at least thinking about it,” Malakar said. “And one of the first few things they talk about is how to govern those assets — assets as in AI models, feature stores and anything that could be used as input into the AI or the machine learning lifecycle.”
Governance, however, is hard. Data governance has been a challenge for enterprises for years. Now, AI governance is taking its place alongside data governance as a requirement as well as a challenge.
Data has long been a driver of business decisions.
For decades, however, data stewardship and analysis were the domain of small teams within organizations. Data was kept on premises, and even high-level executives had to request that IT personnel develop charts, graphs, reports, dashboards and other data assets before they could use them to inform decisions.
The process of requesting information, developing an asset to analyze the information and reaching a decision was lengthy, taking at a minimum a few days and — depending on how many requests were made and the size of the data team — even months. With data so controlled, there was little need for data governance. Then, a bit less than 20 years ago, self-service analytics began to emerge. Vendors such as Tableau and Qlik developed visualization-based platforms that enabled business users to view and analyze data on their own, with proper training.
With data no longer the sole domain of experts — and with trained experts no longer the only ones in control of their organization’s data, and business users empowered to take action on their own — organizations needed guidelines.
And with data in the hands of more people within an enterprise — still only about a quarter of all employees, but more than before — more oversight was needed. Otherwise, organizations risked noncompliance with government regulations and data breaches that could reveal sensitive information or cost a company its competitive advantage.
A similar circumstance is now taking place with AI — albeit at a much faster rate, given all that has happened in less than two years — that necessitates AI governance. Just as data was once largely inaccessible, so was AI. And just as self-service analytics enabled more people within organizations to use data, necessitating data governance, generative AI is enabling more people within organizations to use AI, necessitating AI governance.
Donald Farmer, founder and principal of TreeHive Strategy, noted a similarity between the rising need for AI governance and events that necessitated data governance.
“That is a parallel,” he said. “It’s a reasonable one.”
However, what is happening with AI is taking place much more quickly and on a much larger scale than what happened with self-service analytics, Farmer continued. AI has the potential to completely alter how businesses conduct themselves, if properly governed. Farmer compared what AI can do for today’s enterprises to what electricity did for businesses at the turn of the 20th century. At the time, widespread electrical use was dangerous. In response, organizations employed what were then known as CEOs — chief electricity officers — who oversaw the use of electricity and made sure safety was maintained.
“This is a very fundamental shift that we’re just seeing the start of,” Farmer said. “It’s almost as fundamental as [electricity] — everything you do is going to be affected by AI. The comparison with self-service analytics is accurate, but it’s even more fundamental than that.”
Alation’s Malakar similarly noted parallels to be drawn between self-service analytics and the surging interest in AI. Both are rooted in less-technical employees wanting to use technology to help make decisions and take action.
“What we see is that the business analyst who doesn’t know coding wants less and less reliance on IT,” Malakar said. “They want to be empowered to make decisions that are data-related.” First, that was enabled to some degree by self-service analytics. Now, it can be enabled to a much larger degree by generative AI. Every enterprise has questions such as how to reduce expenses, predict churn or implement the most effective marketing campaign. AI can provide the answers.
And with generative AI, it can provide the answers to virtually any employee.
“They’re all AI/ML questions that were not being asked to the same degree 10 years ago,” Malakar said. “So now all these things like privacy, security, explainability [and] accountability become very important — a lot more important than it was in the world of pure data governance.”
At its core, AI governance is a lot like — and connected to — data governance. Data governance frameworks are documented sets of guidelines to ensure the proper use of data, including policies related to data privacy, quality and security. In addition, data governance includes access controls that limit who can do what with their organization’s data.
AI governance is linked to data governance and essentially builds on it, according to Petrie.
AI governance applies the same standards as data governance — practices and policies designed to ensure the proper use of AI tools and accuracy of AI models and applications. But without good data governance as a foundation, AI governance loses significance.
Before AI models and applications can be effective and used to inform decisions and automate processes, they need to be trained using good, accurate data. “[Data governance and AI governance] are inextricably linked and overlap quite a bit,” Petrie said. “All the risks of AI have predecessors when it comes to data governance. You should view data governance as the essential foundation of AI governance.”
Most enterprises do have data governance frameworks, he continued. But the same cannot be said for AI governance, as Petrie’s 2023 survey demonstrated.
“That signals a real problem,” he said.
The problem could be one that puts an organization at a competitive disadvantage — that they’re not ready to develop and deploy AI models and applications and reap their benefits, while competitors are doing so. Potentially more damaging, however, is if an enterprise is developing and deploying AI tools, but isn’t properly managing how they’re used. Rather than simply holding back growth, this could lead to negative consequences. But AI governance is about more than just protection from potential problems. It’s also about enabling confident use of AI tools, according to Farmer.
Good data governance frameworks strike a balance between putting limits on data use aimed to protect the enterprise from problems and supporting business users so that they can work with data without fearing that they’re going to unintentionally put their organization in a precarious position.
Good AI governance frameworks need to strike that same balance so that someone asking a question of an AI assistant isn’t afraid that the response they get and subsequent action they take will have a negative effect. Instead, that user needs to feel empowered.
“People are beginning to come around to the idea that a well-governed system gives people more confidence in being able to apply it at scale,” Farmer said. “Good governance isn’t a restricting function. It should be an enabling function. If it’s well governed, you give people freedom.” Specific elements of a good framework for AI governance combine belief in the need for a system to manage the use of AI, guidelines that properly enforce the system and technological tools that assist in its execution, according to Petrie.
“AI governance is defining and enforcing policies, standards and rules to mitigate risks related to AI,” he said. “To do that, you need people and process and technology.”
The people aspect starts with executive support for an AI governance program led by someone such as a chief data officer or chief data and analytics officer. Also involved in developing and implementing the framework are those in supporting roles, such as data scientists, data architects and data engineers.
The process aspect is the AI governance framework itself — the policies that address security, privacy, accuracy and accountability. The technology is the infrastructure. Among other tools, it includes data and machine learning observability platforms that look at data quality and pipeline performance, catalogs that organize data and include governance capabilities, master data management capabilities to ensure consistency, and machine learning lifecycle management platforms to train and monitor models and applications.
Together, the elements of AI governance should lead to confidence, according to Malakar. They should lead to conviction in the outputs of AI models and applications so that end users can confidently act. They should also lead to faith that the organization is protected from misuse.
“AI governance is about being able to use AI applications and foster an environment of trust and integrity in the use of those AI applications,” Malakar said. “It’s best practices and accountability. Not every company will be good at each one of [the aspects of AI governance], but if they at least keep those principles in mind, it will lead to better leverage of AI.”
Confidence is perhaps the most significant outcome of a good AI governance framework, according to Farmer. When the data used to feed and train AI models can be trusted, so can the outputs. And when the outputs can be trusted, users can take the actions that lead to growth. Similarly, when the processes automated and overseen by AI tools can be trusted, data scientists, engineers and other experts can use the time they’ve been given by being relieved of mundane tasks to take on new ones that likewise lead to growth.
“The benefit is confidence,” Farmer said. “There’s confidence to do more with it when you’re well governed.”
More tangibly, good AI governance leads to regulatory compliance and avoiding the financial and reputational harm that comes with regulatory violations, according to Petrie. Europe, in particular, has stringent regulations related to AI, and the U.S. is similarly expected to increase regulatory restrictions on exactly what AI developers and deployers can and cannot do.
Beyond regulatory compliance, good AI governance results in good customer relationships, Petrie continued. AI models and applications can provide enterprises with hyperpersonalized information about customers, efficiently enabling personalized shopping experiences and cross-selling opportunities that can increase profits. “Those benefits are significant,” Petrie said. “[But] if you’re going to take something to customers — GenAI in particular — you better make sure you’re getting it right, because you’re playing with your revenue stream.”
If enterprises get generative AI — or traditional AI, for that matter — wrong, i.e., if the governance framework controlling how AI models and applications are developed and deployed is poor, the consequences can be severe.
“All sorts of bad things can happen,” Petrie said.
Some of them are the polar opposite of what can happen when an organization has a good AI governance framework. Instead of regulatory compliance, organizations can wind up with inquisitive regulators, and instead of strong customer relationships, they can wind up with poor ones. But those are the end results.
First, what leads to inquisitive regulators and poor customer relationships, among other things, includes poor accuracy, biased outputs and mishandling of intellectual property.
“If those risks are not properly controlled and mitigated, you can wind up with … regulatory penalties or costs related to compliance, angry or alienated customers, and you can end up with operational processes that hit bottlenecks because the intended efficiency benefits of AI will not be delivered,” Petrie said.
Lack of data security, explainability and accountability are other results of poor AI governance, according to Malakar. Without the combination of good data governance and AI governance, there can be security breaches as well as improperly prepared data — personally identifiable information that hasn’t been anonymized, for example — that seeps into models and gets exposed. In addition, without good governance, it can be difficult to explain and fix bad outputs in a timely fashion or know whom to hold accountable.
“You don’t want to build a model where it can’t be trusted,” Malakar said. “That’s a risk to the entire culture of the company and can drive morale issues.”
Ultimately, just as good AI governance engenders confidence, bad AI governance leads to a lack of confidence, according to Farmer.
If one competing company trusts its AI models and applications and another doesn’t, the one that can act with confidence will reap the benefits, while the other will be stuck in place and miss out on the growth opportunities enabled by generative AI’s significant potential. “Given that the shift is so fundamental, not being well governed is really going to hold you back,” Farmer said. “Governance is the difference between the ability to move swiftly and with confidence, and being held back and taking dangerous risks.”
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
Surging need
Elements of AI governance
Benefits and consequences
Technology
28 Years Later was partially shot on an iPhone 15 Pro Max
Danny Boyle’s zombie sequel 28 Years Later was shot using several iPhone 15 Pro Max smartphones, . This makes it the biggest movie ever made using iPhones, as the budget was around $75 million.
There are some major caveats worth going over. First of all, the sourcing on the story is anonymous, as the film’s staff was required to sign an NDA. Also, the entire film wasn’t shot using last year’s high-end Apple smartphone. Engadget has confirmed that Boyle and his team used a bunch of different cameras, with the iPhone 15 Pro Max being just one tool.
Finally, it’s not like the director just plopped the smartphone on a tripod and called it a day. Each iPhone looks to have been adapted to integrate with full-frame DSLR lenses. Speaking of, those professional-grade lenses cost a small fortune. The phones were also nestled in protective cages.
Even if the phones weren’t exclusively used to make this movie, it’s still something of a full-circle moment for Boyle and his team. The original 28 Days Later was shot primarily on a that cost $4,000 at the time. This camcorder recorded footage to MiniDV tapes.
28 Years Later is the third entry in the franchise and is due to hit theaters in June 2025. The film stars Jodie Comer, Aaron Taylor-Johnson, Ralph Fiennes and Cillian Murphy. This will be the first of three new films . Plot details are non-existent, but all three upcoming movies are being written by Alex Garland. He co-wrote the first one and has since gone on to direct genre fare like Ex Machina, and, most recently, Civil War. He also made a truly underrated .
As for the intersection of smartphones and Hollywood, several films have been shot with iPhones. These include Sean Baker’s Tangerine and Steven Soderbergh’s Unsane.
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