JLL Launches Artificial Intelligence Platform
JLL has released a suite of software services that claim to be the “first comprehensive, ultra-secure AI platform for the commercial real estate...
Read Full ArticleDan Teare examines the ethics around AI emotion detection analysis and looks at potential use cases for facilities managers.
A recent article from Wired.com discussed the news that Network Rail has been using cameras that are equipped with emotion detection analysis, to send automated alerts to staff when it detects certain behaviour such as trespassing or theft. The article sparked significant debate about the ethical implications and potential applications of this technology.
In this Opinion piece, Dan Teare, Founding Partner of DJT Partners gives his insight into the project and busts several myths about this technology.
These AI engines work on models that are trained using video footage. The software effectively watches the footage and learns to recognise patterns. Whether it is cups with a company’s logo being thrown into a bin, or identifying happy, sad, or frustrated faces, the accuracy of these models improves as the data sets behind them grow larger and more diverse.
The project involving emotion detection cameras at Network Rail had its origins in identifying terrorist behaviours and assessing suicide risks at stations. It was accelerated during the pandemic, gaining rapid approval to monitor compliance with face mask mandates at gate lines in major London transport hubs. Some other use cases were tested once the technology was there for feasibility, with facilities service providers being alerted if the cameras identified spillages or crowding, avoiding congestion and potential safety issues.
This technology, which utilises advanced AI, can also be used to analyse human emotions. It opens new possibilities for facilities managers and the built environment, as the potential for such technology to improve service delivery, understand user satisfaction first hand in real-time and maintain or improve security in various environments is immense. However, it also raises important questions about privacy, consent, and the potential for misuse, hence the lively debate on LinkedIn that followed.
The future of this technology in FM looks promising, with advancements in AI and machine learning making it increasingly accurate and reliable. However, the primary concern is privacy. The ability to monitor and analyse emotions in real-time can be perceived as intrusive, especially if individuals are unaware that they are being observed. This could lead to a sense of constant surveillance, eroding trust between occupants and FMs
It’s important to address the concerns raised by sensationalist perspectives like the one presented in Wired, which can sometimes take the implications of such technology out of context. It’s worth noting that we are already under constant surveillance through CCTV systems in public spaces. Emotion detection AI doesn’t take pictures but rather analyses distance points on faces, converting these into numerical patterns to identify emotions like happiness or sadness.
While consent is a critical issue for emotion detection to be ethically implemented, it must be transparent, with clear communication about its use and purpose. It needs to be understood that the businesses or organisations trying to deploy this aren’t gathering data on you as an individual. Arguably the loyalty cards you use when you get to the till, or digital season tickets you use are doing this much more effectively.
"If users frequently display signs of frustration in a particular area of an office, it might indicate problems such as poor lighting, uncomfortable seating, or inadequate climate control, or they may just be stood near a printer that isn’t working, again."
Facilities managers could use emotion detection cameras to monitor and improve the satisfaction levels of occupants in offices, washrooms, and other public areas. By analysing emotions such as frustration, happiness, or stress, FMs can identify and address problem points in their buildings. This has already been done in airports and other locations to help with the passenger experience.
If users frequently display signs of frustration in a particular area of an office, it might indicate problems such as poor lighting, uncomfortable seating, or inadequate climate control, or they may just be stood near a printer that isn’t working, again. Prompt interventions could significantly enhance the overall user experience.
Just as Network Rail aims to enhance safety by detecting behaviours indicative of potential theft or trespassing, similar technology can be employed in other built environments. In malls, airports, or stadiums, emotion detection can help security personnel respond more swiftly to unusual or threatening behaviour.
Emotion detection can also provide insights into how different spaces are being used and perceived, informing maintenance schedules and space utilisation strategies. For example, if a washroom consistently elicits negative emotions, it might be due for a deep clean or renovation.
An evolution of demographic-based AI applications is the use of emotion detection for targeted advertising. Companies are already using AI to identify people based on demographic factors and drive video advertising boards to display relevant content as they pass. For instance, if a camera detects a person pushing a pram, it might trigger adverts for nappies or baby products. Emotion detection takes this a step further by allowing for more nuanced and responsive advertising. If a camera identifies that someone is happy, they might be shown ads for leisure activities, whereas signs of stress might trigger ads for relaxation products.
Instead of changing an advertising board, meeting room or office conditions could be changed, lift music could be tailored to its occupants and favoured smells could be selected on employee profile and sprayed ahead of people based on predictive movement analysis.
To balance the benefits of emotion detection analysis with the associated risks, facilities managers and stakeholders need to adopt a measured and ethical approach:
Ensure that the deployment of emotion detection cameras is transparent. Communicate clearly with occupants about why the technology is being used, how it benefits them, and what measures are in place to protect their privacy.
Implement robust data security protocols to protect sensitive information gathered through emotion detection. Ensure that data is anonymised and stored securely to prevent unauthorised access.
There is the risk of misuse or over-reliance on AI. Emotion detection systems are not infallible and can misinterpret signals, leading to false positives or negatives. Over-reliance on this technology could result in neglecting traditional, human-centric approaches to facilities management, such as direct feedback and personal interaction. Human oversight is crucial to interpret AI findings accurately and make informed decisions.
Develop and adhere to ethical guidelines for the use of AI in facilities management. These should be aligned with broader societal values and legal frameworks to ensure responsible use.
Emotion detection technology offers exciting possibilities for enhancing the built environment and making facilities managers lives better. By providing real-time insights into user satisfaction and behaviour, it can help create more responsive, efficient, and enjoyable spaces. The integration of this technology into targeted advertising represents a natural evolution, further personalising and optimising user experiences.
This is just another piece at the bleeding edge of the AI revolution that when properly harnessed can be used to improve our lives – the question remains to be seen: what is the true price?
Picture: a graphic showing an image of a person with no visible facial features, with their face being scanned. Image Credit: Pixabay
Article written by Dan Teare | Published 24 June 2024
JLL has released a suite of software services that claim to be the “first comprehensive, ultra-secure AI platform for the commercial real estate...
Read Full Article“Liv”, an AI-enabled “digital human”, is now part of Liverpool ONE shopping centre’s front-of-house customer service offering. As part of...
Read Full ArticleUnlock the full potential of IoT in your facilities with these five expert tips, ensuring efficiency, cost-effectiveness, and enhanced management capabilities. In this...
Read Full ArticleAI checkouts have ushered in a new era of data-driven decision-making, transforming how FMs manage their catering operations. In this Opinion piece, Sergii...
Read Full ArticleA new research project won by Birmingham City University, Leeds Beckett University and London South Bank University will explore generative AI in...
Read Full ArticleThe governor of the Bank of England predicts that society will “learn to work with” AI rather than it becoming a "mass destroyer of...
Read Full ArticleA new AI-powered tool to support engineers when repairing hazardous area motors is being developed in the UK. Innovate UK, The Association of Electrical and Mechanical...
Read Full Article2023's final Spotlight Interview is with Andrew Fitzpatrick, a former civil engineer who has worked on highly complex construction projects, including the...
Read Full ArticleEvotech has launched myBEMS AI, a revolutionary range of machine learning solutions aimed at optimising building HVAC systems, reducing energy consumption, and slashing...
Read Full ArticleISS has produced a guide to help facilities managers deploy AI in collaboration with Inma Martinez, a participant at the UK’s first AI Safety...
Read Full Article