From its impact on education to its role in the recent Hollywood strikes – not to mention some dire warnings about the “existential threat” it might present – there can be little doubt that 2023 was the year of artificial intelligence (AI). AI has been one of the defining topics of the past 12 months and will continue to dominate attention throughout 2024 and beyond.
That AI is now the subject of mainstream conversation outside of sci-fi blockbusters is hardly surprising. While virtual assistants like Siri and Alexa helped to lay the foundations for AI as a constant co-pilot, generative technologies like ChatGPT and Midjourney have taken things to another level. As time goes by, AI will continue to have an even greater impact on our daily lives.
Over the longer term, that has implications across numerous areas. From the way we live to the way we work, AI has the potential to redefine our entire existence. In the shorter term, though, there will be some major hurdles to navigate – not least the fact that people will become increasingly aware about AI’s role in corporate decision-making.
Take the financial services sector, for example. As AI becomes more prevalent within the world of banks and insurance companies, consumers will undoubtedly want to know how decisions affecting their financial future are being made. Areas like healthcare and government are likely to attract similar scrutiny, particularly when third-party organisations happen to be involved.
Other industries will also be drawn into that conversation, though – retail among them. Here, AI has the potential to play a role in everything from pricing and promotions through to the personalisation of the customer experience; in fact, with AI subsets like machine learning taken into account, it is already. The key difference is that, as awareness of AI continues to grow, so too will the amount of attention paid to its responsible use.
As a data science company, and one that uses AI within many of its own products and services, it’s only natural that we have an interest in this issue. That’s why we’ve been hard at work on a programme that considers responsible AI, both within dunnhumby, and across the sector as a whole.
Ethics isn’t a new issue for us, particularly when it comes to data science. Our focus on “customer first” principles is born out of the belief that, since data can provide retailers and brands with deep insight into shopper behaviours, those organisations have a responsibility to use that information in a way that benefits their customers.
In many ways, responsible AI is just a subset of data ethics. The situation is far more complex when it comes to AI, though, primarily due to the speed at which the market is moving. Despite only making its public debut on November 30th 2022, for instance, ChatGPT now has more than 100m weekly active users.
That lightning fast pace can make it difficult to keep up – not least for regulators and legislators. The European Union introduced the first ever AI Act this year, but that remains at a relatively early stage. The US’s Blueprint for a Bill of AI Rights is similarly nascent, and is further complicated by the country’s state-by-state approach to enforcement.
In lieu of a centralised set of guidelines to follow, most organisations are instead adopting voluntary ones. More often than not, these tend to echo the “soft laws” outlined by the likes of the OECD, Microsoft, Google, and UNESCO – all of which have their own principles about the creation of responsible AI. Broadly speaking, those principles typically cover five specific areas:
Of those five, some are easier to manage than others. With the right controls in place, considerations like safety, transparency, and accountability can be relatively simple, particularly if an organisation already has robust data privacy standards. Other topics, though, are a little trickier to get right – with fairness being the prime example.
While the definition is undoubtedly up for debate, we tend to think about fairness like this: if two people behave in the same way, then they should be treated in the same way too. What that means from a data science and AI perspective is that, if two people buy the same things, spend the same amount, and shop with the same frequency, then they should be treated identically.
The benefit of thinking about fairness in this way is that it makes any disparities in your own data much easier to detect. Moreover, if you do spot any indicators of unfairness, it then becomes possible to investigate further and see why that might be happening.
Where this gets particularly interesting is that it runs completely contrary to the normal way of thinking about unfairness. Race, age, gender, sexual orientation: all these things are invisible within the data. So, rather than starting with those qualities and then looking for signs of discrimination, you can instead start at the point of discrimination and work backwards – learning along the way how your data model has allowed that to happen.
Reaching that level of understanding is important, too, because it can have a real impact on the end customer. If one of our identically-behaved customers above received 200 coupons per year, and the other only 10, that less fortunate one would understandably want to know why. Very quickly, that takes us from fairness into areas like explainability, contestability, and redress – one of many reasons that we’re so focused on that primary issue.
To that end, we have established a cross-functional team to explore fairness alongside those other guiding principles of responsible AI. Our legal and data science teams are actively involved, and we also have access to external expertise in this area. Their fresh eyes and fresh insights are helping us to sharpen our thinking around this critical issue.
Our progress so far is exciting. Already, we have started to explore algorithms that are specifically designed to find and measure fairness. We have also begun to look for unfairness in our own data, not least our ability to explain it should we find it. Ultimately, this is important to us, because it is important to our clients; just like their own customers, retailers and brands will need to be confident in the responsible use of AI, too.
Do we have all of the answers to the responsible application of AI, then? No – and nobody does. But the journey in search of them is one we’re excited to take. I look forward to sharing more in the future.
AI holds huge potential. It can deliver incredible things. Ensuring that it delivers them in a responsible, customer first way should be a priority for us all.
A look at dunnhumby’s unique Customer Data Science, which is at the core of everything we do.
Combining the latest techniques, algorithms, processes and applicationsUnlock the value of your data assets
Govern data more effectively and manage risk confidentlyCookie | Description |
---|---|
cli_user_preference | The cookie is set by the GDPR Cookie Consent plugin and is used to store the yes/no selection the consent given for cookie usage. It does not store any personal data. |
cookielawinfo-checkbox-advertisement | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category . |
cookielawinfo-checkbox-analytics | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category . |
cookielawinfo-checkbox-necessary | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
CookieLawInfoConsent | The cookie is set by the GDPR Cookie Consent plugin and is used to store the summary of the consent given for cookie usage. It does not store any personal data. |
viewed_cookie_policy | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
wsaffinity | Set by the dunnhumby website, that allows all subsequent traffic and requests from an initial client session to be passed to the same server in the pool. Session affinity is also referred to as session persistence, server affinity, server persistence, or server sticky. |
Cookie | Description |
---|---|
wordpress_test_cookie | WordPress cookie to read if cookies can be placed, and lasts for the session. |
wp_lang | This cookie is used to remember the language chosen by the user while browsing. |
Cookie | Description |
---|---|
CONSENT | YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data. |
vuid | Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos to the website. |
_ga | The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors. |
_gat_gtag_UA_* | This cookie is installed by Google Analytics to store the website's unique user ID. |
_ga_* | Set by Google Analytics to persist session state. |
_gid | Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously. |
_hjSessionUser_{site_id} | This cookie is set by the provider Hotjar to store a unique user ID for session tracking and analytics purposes. |
_hjSession_{site_id} | This cookie is set by the provider Hotjar to store a unique session ID, enabling session recording and behavior analysis. |
_hp2_id_* | This cookie is set by the provider Hotjar to store a unique visitor identifier for tracking user behavior and session information. |
_hp2_props.* | This cookie is set by the provider Hotjar to store user properties and session information for behavior analysis and insights. |
_hp2_ses_props.* | This cookie is set by the provider Hotjar to store session-specific properties and data for tracking user behavior during a session. |
_lfa | This cookie is set by the provider Leadfeeder to identify the IP address of devices visiting the website, in order to retarget multiple users routing from the same IP address. |
Cookie | Description |
---|---|
aam_uuid | Set by LinkedIn, for ID sync for Adobe Audience Manager. |
AEC | Set by Google, ‘AEC’ cookies ensure that requests within a browsing session are made by the user, and not by other sites. These cookies prevent malicious sites from acting on behalf of a user without that user’s knowledge. |
AMCVS_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, indicates the start of a session for Adobe Experience Cloud. |
AMCV_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, Unique Identifier for Adobe Experience Cloud. |
AnalyticsSyncHistory | Set by LinkedIn, used to store information about the time a sync with the lms_analytics cookie took place for users in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
bcookie | LinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognise browser ID. |
bscookie | LinkedIn sets this cookie to store performed actions on the website. |
DV | Set by Google, used for the purpose of targeted advertising, to collect information about how visitors use our site. |
ELOQUA | This cookie is set by Eloqua Marketing Automation Tool. It contains a unique identifier to recognise returning visitors and track their visit data across multiple visits and multiple OpenText Websites. This data is logged in pseudonymised form, unless a visitor provides us with their personal data through creating a profile, such as when signing up for events or for downloading information that is not available to the public. |
gpv_pn | Set by LinkedIn, used to retain and fetch previous page visited in Adobe Analytics. |
lang | Session-based cookie, set by LinkedIn, used to set default locale/language. |
lidc | LinkedIn sets the lidc cookie to facilitate data center selection. |
lidc | Set by LinkedIn, used for routing from Share buttons and ad tags. |
li_gc | Set by LinkedIn to store consent of guests regarding the use of cookies for non-essential purposes. |
li_sugr | Set by LinkedIn, used to make a probabilistic match of a user's identity outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
lms_analytics | Set by LinkedIn to identify LinkedIn Members in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland) for analytics. |
NID | Set by Google, registers a unique ID that identifies a returning user’s device. The ID is used for targeted ads. |
OGP / OGPC | Set by Google, cookie enables the functionality of Google Maps. |
OTZ | Set by Google, used to support Google’s advertising services. This cookie is used by Google Analytics to provide an analysis of website visitors in aggregate. |
s_cc | Set by LinkedIn, used to determine if cookies are enabled for Adobe Analytics. |
s_ips | Set by LinkedIn, tracks percent of page viewed. |
s_plt | Set by LinkedIn, this cookie tracks the time that the previous page took to load. |
s_pltp | Set by LinkedIn, this cookie provides page name value (URL) for use by Adobe Analytics. |
s_ppv | Set by LinkedIn, used by Adobe Analytics to retain and fetch what percentage of a page was viewed. |
s_sq | Set by LinkedIn, used to store information about the previous link that was clicked on by the user by Adobe Analytics. |
s_tp | Set by LinkedIn, this cookie measures a visitor’s scroll activity to see how much of a page they view before moving on to another page. |
s_tslv | Set by LinkedIn, used to retain and fetch time since last visit in Adobe Analytics. |
test_cookie | Set by doubleclick.net (part of Google), the purpose of the cookie is to determine if the users' browser supports cookies. |
U | Set by LinkedIn, Browser Identifier for users outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
UserMatchHistory | LinkedIn sets this cookie for LinkedIn Ads ID syncing. |
UserMatchHistory | This cookie is used by LinkedIn Ads to help dunnhumby measure advertising performance. More information can be found in their cookie policy. |
VISITOR_INFO1_LIVE | A cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface. |
YSC | YSC cookie is set by YouTube and is used to track the views of embedded videos on YouTube pages. |
yt-remote-connected-devices | YouTube sets this cookie to store the video preferences of the user using embedded YouTube video. |
yt-remote-device-id | YouTube sets this cookie to store the video preferences of the user using embedded YouTube video. |
yt.innertube::nextId | This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen. |
yt.innertube::requests | This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen. |
_gcl_au | Set by Google Analytics, to take information in advert clicks and store it in a 1st party cookie so that conversions can be attributed outside of the landing page. |