The US investment regulator, the Securities and Exchange Commission (SEC), has dished out penalties totalling $400,000 to two investment companies who made misleading claims about how they used AI, a practice dubbed ‘AI Washing’.

What Is AI Washing? 

The term ‘AI washing’ (as used by the investment regulator in this case) refers to the practice of making unsubstantiated or misleading claims about the intelligence or capabilities of a technology product, system, or service in order to give it the appearance of being more advanced (or artificially intelligent) than it actually is.

For example, this can involve overstating the role of AI in products or exaggerating the sophistication of the technology, with the goal often being to attract attention, investment, or market-share by capitalising on the hype and interest surrounding AI technologies.

What Happened? 

In this case, two investment advice companies, Delphia (USA) Inc. and Global Predictions Inc., were judged by the SEC to have made false and misleading statements about their purported use of artificial intelligence (AI).

Delphia 

For example, in the case of Toronto-based Delphia (USA) Inc, the SEC said that from 2019 to 2023, the firm made “false and misleading statements in its SEC filings, in a press release, and on its website regarding its purported use of AI and machine learning that incorporated client data in its investment process”. Delphia claimed that it “put[s] collective data to work to make our artificial intelligence smarter so it can predict which companies and trends are about to make it big and invest in them before everyone else.”  Following the SEC’s investigation, the SEC concluded that Delphia’s statements were false and misleading because it didn’t have the AI and machine learning capabilities that it claimed. Delphia was also charged by the SEC with violating the Marketing Rule, which (among other things) prohibits a registered investment adviser from disseminating any advertisement that includes any untrue statement of material fact.

Delphia neither confirmed nor denied the SEC’s charges but agreed to pay a substantial civil penalty of $225,000.

Global Predictions

In the case of San Franciso-based Global Predictions, the SEC says it made false and misleading claims in 2023 on its website and on social media about its purported use of AI. An example cited by the SEC is that Global Predictions falsely claimed to be the “first regulated AI financial advisor” and misrepresented that its platform provided “expert AI-driven forecasts.” Like Delphia, Global Predictions was also found to have violated the Marketing Rule, falsely claiming that it offered tax-loss harvesting services and included an impermissible liability hedge clause in its advisory contract, among other securities law violations.

Following the SEC’s judgement, Global Predictions also neither confirmed nor denied it and agreed to pay a civil penalty of $175,000.

Investor Alert Issued

The cases of the two investment firms prompted the SEC’s Office of Investor Education and Advocacy to issue a joint ‘Investor Alert’ with the North American Securities Administrators Association (NASAA), and the Financial Industry Regulatory Authority (FINRA) about artificial intelligence and investment fraud.

In the alert, the regulators highlighted the need to “make investors aware of the increase of investment frauds involving the purported use of artificial intelligence (AI) and other emerging technologies.”   

The alert flagged up how “scammers are running investment schemes that seek to leverage the popularity of AI. Be wary of claims — even from registered firms and professionals — that AI can guarantee amazing investment returns” using “unrealistic claims like, ‘Our proprietary AI trading system can’t lose!’ or ‘Use AI to Pick Guaranteed Stock Winners!” 

Beware ‘Pump-and-Dump’ Schemes 

In the alert, the regulators also warned about how “bad actors might use catchy AI-related buzzwords and make claims that their companies or business strategies guarantee huge gains” and how claims about a public company’s products and services relating to AI also might be part of a pump-and-dump scheme. This is a scheme where scammers falsely present an exaggerated view of a company’s stock through misleading positive information online, causing its price to rise as investors rush to buy. The scammers then sell their shares at this inflated price. Once they’ve made their profit and stop promoting the stock, its price crashes, leaving other investors with significant losses.

AI Deepfake Warning 

The regulators also warned of how AI-enabled technology is being used to scam investors using “deepfake” video and audio. Examples of this highlighted by the regulators include:

– Using audio to try to lure older investors into thinking a grandchild is in financial distress and in need of money.

– Scammers using deepfake videos to imitate the CEO of a company announcing false news in an attempt to manipulate the price of a stock.

– Scammers using AI technology to produce realistic-looking websites or marketing materials to promote fake investments or fraudulent schemes.

– Bad actors even impersonating SEC staff and other government officials.

The regulators also highlight high scammers now often use celebrity endorsements (as they have in the UK using Martin Lewis’s name and image without consent). The SEC in the US says making an investment decision just because someone famous says a product or service is a good investment is never a good idea.

Don’t Just Rely On AI-Generated Information For Investments 

In the alert, the US regulators also warn against relying solely on AI-generated information in making investment decisions, e.g. to predict changes in the stock market’s direction or the price of a security. They highlight how AI-generated information might rely on data that is inaccurate, incomplete, or misleading, or how it could be based on false or outdated information about financial, political, or other news events. Also, it could draw from false or misleading information.

Advice 

The alert offers plenty of advice on how to avoid falling victim to AI-based financial and investment scams with the overriding message being that “Investment claims that sound too good to be true usually are.” The regulators stress the importance of checking credentials and claims, working with registered professionals, and making use of the regulators.

What Does This Mean For Your Business? 

Just as a lack of knowledge about cryptocurrencies has been exploited by fraudsters in Bitcoin scams, regulators are now keen to highlight how a lack of knowledge about AI and its capabilities are now being exploited by bad actors in a similar way.

AI may have many obvious benefits, but the message here, as highlighted by the much-publicised substantial fines given to the two investment companies and the alert issued by regulators to beware ‘too good to be true’ AI claims. The regulators have highlighted how AI is now being exploited for bad purposes in a number of different ways. These include deepfakes and pump-and-dump schemes, via different channels, all of which are designed to exploit the emotions and aspirations of investors, and to build trust to the point where they suspend any critical analysis of what they’re seeing and reading and react impulsively.

With generative AI (e.g. AI images, videos, and AI audio cloning) now becoming so much more realistic and advanced to the point where governments in a key election year are issuing warnings and AI models are being limited on what they can respond to (refer Gemini with election questions), the warning signs are there for financial investors. This story also serves as an example to companies to be very careful about how they represent their usage of AI, what message this gives to customers, and whether claims can be substantiated. It’s likely that we’ll see much more ‘AI washing’ in the near future

In this tech insight, we look at what customer journey mapping is, its benefits, the challenges of using it, and also we look at some of the popular customer journey mapping software solutions available.

What Is Customer Journey Mapping?

Customer journey mapping refers to a strategic process (that’s used by marketers) to visualise and understand the complete experience of a customer interacting with a product, service, or brand from the customer’s perspective. It’s a visual representation of the different interactions customers have with your brand, product, or service until they decide to purchase it from your business (and what happens beyond).

Identifying Key Interactions 

The customer journey mapping process involves identifying key interactions that the customer has with the organisation, understanding the customer’s feelings, motivations, and questions at each step, and recognising opportunities for improvement.

The map typically starts from the initial awareness or need recognition stage, through various touchpoints such as research, purchase, and post-purchase experiences, ending with loyalty or advocacy.

Who Does It? 

Broadly speaking, it’s used by marketing teams because they are directly involved in understanding and communicating with the target audience. Also, customer journey mapping can give marketers the kind of deeper understanding of customers’ experiences that enables them to improve how they target and serve prospects, which can ultimately deliver increased sales and loyalty.

More specifically, customer journey mapping is also carried out by:

– Product managers and development teams who use it to ensure that the product or service meets the customers’ needs and expectations at every point.

– Customer experience (CX) professionals, i.e. those specialising in understanding and improving the interaction between an organisation and its customers, and who want to identify gaps in the customer experience.

– User experience (UX) designers. These focus on the usability and overall experience of digital interfaces and tend to use journey maps to visualise how users interact with a website or app and identify areas for improvement.

– Service designers / those involved in designing and improving entire service processes, who use customer journey mapping to ensure that every touchpoint is optimised for the best customer experience.

– Senior managers who may also be involved in producing and reviewing the customer journey maps to make strategic decisions that align with customer needs and organisational goals.

Why Use It? 

Some of the key reasons for conducting customer journey mapping include:

– Enhancing customer understanding, i.e. helping organisations to see things from a customer’s viewpoint, leading to deeper insights into their needs and preferences.

– Identifying ‘pain points’ and bottlenecks – where customers face difficulties or get stuck, thereby allowing for prioritisation of improvements.

– Improving customer satisfaction, loyalty, and advocacy by addressing issues and optimising the journey.

– Aligning teams around the customer experience by providing a shared understanding across departments.

– Driving and informing strategic business strategies and decisions, such as for product development, and service improvements that align with delivering customer value.

– Optimising ‘touchpoints’ and channels – helping understand and optimise interactions and leveraging high-performing channels for a cohesive experience.

– Identifying gaps in the marketing strategy, e.g. by revealing channels and touchpoints that aren’t being used effectively, thus offering opportunities for optimisation.

Common Challenges

Although customer journey mapping can be very useful and deliver some important insights, it’s not without its challenges. For example, some popular challenges faced by marketers trying to use this type of mapping effectively include:

– Distinguishing fact from assumption. It’s crucial to rely on data to ensure the journey map accurately reflects actual customer behaviours rather than assumptions about how customers might interact with the company.

– Ensuring map accuracy. Inaccurate mapping can lead to misguided strategic decisions, potentially wasting resources and missing key opportunities to enhance the customer experience.

– Incorporating all touchpoints. For example, customers may interact with a brand through quite a variety of channels and actions, making it challenging to capture and understand every possible step in their journey.

– Dealing with the complexity of such a map. Comprehensive journey maps can become very detailed and complex, making them difficult to create, understand, and use effectively.

– Keeping maps updated. This is because customer behaviours and preferences evolve over time, necessitating regular updates to the journey maps to keep them relevant and useful.

– Tracking improvements. Once changes are made based on journey map insights, it’s important to measure their impact to ensure they’re driving the desired outcomes.

– Resource intensiveness. The process of creating, maintaining, and updating customer journey maps can be time-consuming and require significant effort from various team members, straining marketing resources.

– Adapting to digital tools. While traditional paper-based mapping can be cumbersome, transitioning to digital tools for journey mapping (i.e. customer journey mapping software), may involve a learning-curve and require additional resources.

Tackling The Challenges By Using Customer Journey Mapping Software 

As mentioned above, customer journey mapping software offers several key benefits to tackle the challenges of journey mapping efficiently, such as:

– Real-time data Integration, i.e. it enables accurate, live reflections of customers’ behaviour, facilitating quick strategic adjustments.

– Dynamic viewing and filtering. It simplifies the updating process, allows for easy navigation of insights, and supports decision-making with filterable maps.

– It helps deliver personalised experiences / tailored customer journeys by segment, improving conversion and satisfaction rates through continuous optimisation.

– Efficiency and simplicity, thereby transforming previously time-consuming tasks into quick and straightforward processes, eliminating the need for physical mapping materials.

– Enhanced collaboration by facilitating sharing across the organisation, allowing teams to focus on relevant touchpoints and insights, promoting a customer-centric culture.

Popular Customer Journey Mapping Software

Here are some examples of popular customer journey mapping software options for businesses and organisations of different sizes, some of whose names you may already be familiar with (particularly Microsoft):

Microsoft Dynamics 365 Customer Insights 

This provides an AI-driven customer data platform that combines customer journey mapping with actionable insights, predictive analytics, and personalisation options. Since it’s from Microsoft, a significant advantage is that it integrates seamlessly with other Microsoft products that a businesses probably already uses. It’s perhaps most suitable for medium to large enterprises looking for a comprehensive solution that not only maps customer journeys but also leverages AI to drive decision-making and personalised customer engagements.

HubSpot

Features/benefits include integrating customer journey mapping with CRM, marketing, sales, and service hubs, offering a comprehensive view of the customer journey. Features include email marketing, lead management, analytics, and automation tools.

This platform is suitable for businesses of all sizes due to its scalable platform, while HubSpot is particularly beneficial for those looking to integrate their customer journey mapping with a broader inbound marketing and sales strategy.

Salesforce Journey Builder 

Part of the Salesforce Marketing Cloud, this tool allows for the creation of personalised customer journeys across various channels and devices. It offers powerful segmentation capabilities, real-time interaction management, and analytics.

Salesforce Journey Builder may be ideal for medium to large businesses already invested in the Salesforce ecosystem, seeking to leverage advanced customer journey mapping with extensive customisation and integration options.

Miro 

This is a collaborative online whiteboard platform that’s quite versatile, enabling the visual mapping of customer journeys, brainstorming sessions, and project planning. It supports real-time collaboration, making it easy to work with teams remotely. Miro is well-suited for businesses of all sizes, especially those that value collaboration and flexibility in their planning and customer experience design processes.

Smaply 

This software offers detailed journey maps, persona creation, and stakeholder maps. It’s designed to provide a clear visualisation of customer experiences, including pain points and emotions, with exportable and shareable maps. Smaply may be best suited to SMEs or teams within larger organisations focused on service design and customer experience improvement projects.

Adobe Experience Platform 

This is a robust platform capable of delivering personalised customer experiences at scale, with real-time customer profiles, predictive analytics, and cross-channel journey orchestration. It’s probably ideal for large enterprises that require a powerful platform to manage complex customer journeys and deliver personalised experiences across various touchpoints.

What Does This Mean For Your Business? 

For UK businesses, the use of customer journey mapping (and popular customer journey mapping software) is helping to meet the need for a more nuanced understanding of the customer experience. By being able to clearly visualise the entire journey from initial awareness through to loyalty and advocacy, businesses can gain invaluable insights into customer interactions, pain points, and so-called ‘moments of delight.’ This strategic process not only helps businesses gain a deeper comprehension of customer needs and preferences but also highlights areas for improvement. In this way, it can help drive strategic decisions that enhance customer satisfaction and loyalty which, of course, can be of huge benefit to businesses.

Customer journey mapping software offers a way to address the common challenges associated with traditional mapping methods, i.e. it gives real-time data integration, dynamic viewing, and filtering capabilities, plus the ability to deliver personalised experiences. These software tools streamline the mapping process, making it faster, more accurate, and less resource-intensive, and facilitate collaboration across departments, ensuring a unified approach to improving the customer experience.

Businesses not currently leveraging customer journey mapping (software) therefore stand to gain a competitive edge by adopting it. The insights derived from journey maps can guide more effective marketing strategies, product development, and customer service improvements. Also, the use of customer journey mapping software can significantly reduce the time and effort required to create and maintain accurate maps, thereby saving costs, reducing risk, and allowing businesses to quickly adapt to changes in customer behaviour and market conditions.

In summary then, customer journey-mapping and the adoption of specialised software to facilitate this process offer businesses the opportunity to transform their understanding of the customer experience which can translate into greater business success. In a landscape where customer expectations are ever-evolving, the ability to swiftly and effectively respond to these changes is not just advantageous but essential.

It’s been reported that Glassdoor (the website that allows current employees to anonymously review their employer) posted users’ real names to their profiles without their consent.

What Is Glassdoor? 

By allowing users to register anonymously, Glassdoor is a website that allows current and former employees to anonymously review their companies and management. Founded in 2007 in Mill Valley, California, the platform is used for obtaining insights into company cultures, salaries, and interview processes. Its aim is to foster workplace transparency, enabling job seekers to make better-informed decisions about their careers by learning from the experiences of others.

Reported 

Unfortunately for Glassdoor, a user’s account (taken from her personal blog) of her recent negative experience with Glassdoor (following her contacting Glassdoor’s customer support ) has been widely reported in the press.

Added Name To Profile 

Following the lady (reportedly named Monica) sending an email to Glassdoor’s customer support that showed her full name in the ‘From’ line, Monica alleges that she then discovered that Glassdoor had updated her profile by adding her real name and location (the name pulled from the email), without her consent.

Users Leaving Glassdoor 

It’s been reported that the experience of Monica, identified as a Midwest-based software professional who joined Glassdoor 10 years ago, has now led to other members leaving the platform over fears they could also be ‘outed’. Not only could this be regarded as a breach of trust of the anonymity and privacy that users signed up with but could also have adverse employment consequences from employer retaliation.

Following reports of Monica’s experience in the media, it’s been reported that another user, identified as Josh Simmons, has also said Glassdoor added information about him to his personal profile, again without his consent.

Had To Delete Account 

It’s been reported that although Glassdoor’s privacy policy states “If we have collected and processed your personal information with your consent, then you can withdraw your consent at any time,”  Monica claims that she was not given this option, that Glassdoor stored her name, and that her only recommended option to remove her details was to delete her account altogether. Deleting also meant deleting her reviews.

Shared With Fishbowl

One of the complications of the case appears to be the fact that Glassdoor was integrated with Fishbowl (an app for work-related discussions), three years ago. This led to:

– Glassdoor now saying that it “may update your Profile with information we obtain from third parties. We may also use personal data you provide to us via your resume(s) or our other services.” 

– Glassdoor staff reportedly consult publicly-available sources of information to verify information that is then used to update users’ Glassdoor accounts, in order to improve the accuracy of information for Fishbowl users.

– Glassdoor updating users’ profiles without notifying the user, e.g. if inaccuracies are found, because of its commitment to keeping Fishbowl’s information accurate.

What Does Glassdoor Say? 

Glassdoor has issued a statement saying: “Glassdoor is committed to providing a platform for people to share their opinions and experiences about their jobs and companies, anonymously – without fear of intimidation or retaliation. User reviews on Glassdoor have always and will always be anonymous.” 

What Does This Mean For Your Business? 

A large part of the value of Glassdoor is the fact that users are willing to share their ‘honest’ views about their employers and managers. One of the key reasons they feel able to do so is the anonymity that they had during registration and the assumption that this would remain and that their privacy would be protected. However, if reports are to be believed, integration with and cross-pollination between Fishbowl and Glassdoor has led to policy changes and a new approach whereby a user’s details can be updated, allegedly without consent, and obtained from other sources thereby potentially meaning that users could be unmasked to employers.

The widely publicised stories of this allegedly happening appear likely to have damaged a key source of Glassdoor’s value – the trust that users have that their anonymity will be protected. This may explain why users are reportedly leaving the platform. This story illustrates how important matters of data protection are to businesses and individuals, particularly around privacy and consent, plus how risks can increase for users if aspects of data protection are damaged and changed.

The consequences of putting users in what could be described as a difficult and risky position could potentially be severe and/or long-lasting damage for Glassdoor’s business and reputation.

A new study published in The Lancet shows how an AI tool called Foresight (which fully analyses patient health records and makes digital twins of patients) could be used to predict the future of your health.

What Is Foresight?

The Foresight tool is described by the researchers as a “generative transformer in temporal modelling of patient data, integrating both free text and structured formats.” In other words, it’s a sophisticated AI system that’s designed to analyse patient health records over time.

What Does It All Mean? 

The “generative transformer” type of AI is a machine learning / large language model (an ‘LLM’) that can generate new data based on what it has learned from previous data. The term “transformer” is a specific kind of model that’s very good at handling sequences of data, like sentences in a paragraph or a series of patient health records over time (temporal), i.e. a patient’s electronic health records (EHR).

Unlike other health prediction models, Foresight can use a much wider range of data in different formats. For example, Foresight can use everything from medical history, diagnosis, treatment plans, and outcomes, in both free text formats like (unorganised) doctors’ notes or radiology reports and more structured formats. These can include database entries or spreadsheets (with specific fields for patient age, diagnosis codes, or treatment dates).

 Why? 

The researchers say that the study is aimed to evaluate how effective Foresight is in the modelling of patient data and using it to predict a diverse array of future medical outcomes, such as disorders, substances (such as to do with medicines, allergies, or poisonings), procedures, and findings (including relating to observations, judgements, or assessments).

The Foresight Difference 

The researchers say that the difference between Foresight and existing approaches to model a patient’s health trajectory focus mostly on structured data and a subset of single-domain outcomes is that Foresight can take a lot more diverse types and formats of data into account.

Also, being an AI model, Foresight can easily scale to more patients, hospitals, or disorders with minimal or no modifications, and like other AI models that ‘learn,’ the more data it receives, the better it gets at using that data.

How Does It Work? (The Method) 

The method tested in a recent study involved Foresight working in several steps. In the research, the Foresight AI tool was tested across three different hospitals, covering both physical and mental health, and five clinicians performed an independent test by simulating patients and outcomes.

In the multistage process, the researchers trained the AI models on medical records and then fed Foresight new healthcare data to create virtual duplicates of patients, i.e. ‘digital twins’. The digital twins of patients could then be used to forecast different outcomes relating to their possible/likely disease development and medication needs, i.e. educated guesses were produced about any future health issues, like illnesses or treatments that might occur for a patient.

The Findings 

The main findings of the research were that the Foresight AI tool and the use of digital twins can be used for real-world risk forecasting, virtual trials, and clinical research to study the progression of disorders, to simulate interventions and counterfactuals, and for educational purposes. The researchers said that using this method, they demonstrated that Foresight can forecast multiple concepts into the future and generate whole patient timelines given just a short prompt.

What Does This Mean For Your Business? 

Using an AI tool that can take account of a wider range of patient health data than other methods, make a digital twin, produce simulations, and forecast possible health issues and treatments in the future, i.e. whole patient timelines until death could have many advantages. For example, as noted by the researchers, it could help medical students to engage in interactive learning experiences by simulating medical case studies. This could help them to practice clinical reasoning and decision-making in a safe environment, as well as helping them with ethical training by facilitating discussions on fairness and bias in medicine.

This kind of AI medical prediction-making could also be useful in helping doctors to alert patients to tests they may need to take to enable better disease-prevention as well as helping with issues such as medical resource planning.  However, as many AI companies say, feeding personal and private details (medical records) into AI is not without risk in terms of privacy and data protection. Also, the researchers noted that more tests are needed to validate and test the performance of the model on long simulations. One other important point to remember is that regardless of current testing of the model, Foresight is currently predicting things long into the future for patients and, as such, it’s not yet known how accurate its predictions are.

Following more testing (as long as issues like security, consent, and privacy are adequately addressed) a fully developed method of AI-based health issue prediction could prove to be very valuable to medical professionals and patients and could create new opportunities in areas and sectors related to health, such as fitness, wellbeing,  pharmaceuticals, insurance, and many more.

US researchers have reported discovering a hardware chip vulnerability inside Apple M1, M2, and M3 silicon chips. The unpatchable ‘GoFetch’ is a microarchitecture vulnerability and side-channel attack that reportedly affects all kinds of encryption algorithms, even the 2,048-bit keys that are hardened to protect against attacks from quantum computers.

This serious vulnerability renders the security effects of constant-time programming (a side-channel mitigation encryption algorithm) useless. This means that encryption software can be tricked by applications using GoFetch into putting sensitive data into the cache so it can be stolen.

Pending any fix advice from Apple, users are recommended to use the latest versions of software, and to perform updates regularly. Also, developers of cryptographic libraries should set the DOIT bit and DIT bit bits (disabling the DMP on some CPUs) and to use input blinding (cryptography). Users are also recommended to avoid hardware sharing to help maintain the security of cryptographic protocols.

Microsoft is making a security-focused policy change that will see RSA keys with lengths shorter than 2048 bits deprecated. RSA keys are algorithms used for secure data encryption and decryption in digital communications, i.e. to encrypt data for secure communications over an enterprise network.

However, with RSA encryption keys becoming vulnerable to advancing cryptographic techniques (driven by advancements in compute power) the decision by Microsoft to depreciate them is being seen as a way to stop organisations from using what is now seen as a weaker method of authentication.

Also, the move by Microsoft will help bring the industry in line with recommendations from the internet standards and regulatory bodies who banned the use of 1024-bit keys in 2013 and recommended that RSA keys should have a key length of 2048 bits or longer.