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{{Paper
|id=Vol-2737/short paper02
|storemode=property
|title=Conceptualizations Towards an Ethical Framework for Applying Artificial Intelligence in Facility Management
|pdfUrl=https://ceur-ws.org/Vol-2737/SP_2.pdf
|volume=Vol-2737
|authors=Juho Vaiste
|dblpUrl=https://dblp.org/rec/conf/tethics/Vaiste20
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==Conceptualizations Towards an Ethical Framework for Applying Artificial Intelligence in Facility Management==
https://ceur-ws.org/Vol-2737/SP_2.pdf
Proceedings of the Conference on Technology Ethics 2020 - Tethics 2020
Conceptualizations towards an ethical framework for
applying artificial intelligence in facility management
Short paper
Juho Vaiste1 [0000-0002-4353-6388]
1 University of Turku, Turku, Finland
juho.vaiste@utu.fi
Abstract. Facility management faces new opportunities and challenges through
the emerging solutions of artificial intelligence (AI) technologies. With powerful
technologies, great responsibility follows. Ethics of AI technologies has been
recognized as an essential field of research and an integral part of applying AI.
By creating an ethical framework, we can ensure both ethically aligned conduct
and efficient and innovative adoption of AI technologies in facility management.
Keywords: Ethics, Artificial Intelligence, Facility Management
1 Introduction
Facility management faces new opportunities and challenges through the emerging
solutions of artificial intelligence (AI) technologies. Facility management is defined as
a multidisciplinary field ensuring functionality, comfort, safety and efficiency in the
built environments (IFMA, 2020). The rise of AI technologies attaches to the
continuum of digitalization and thus is the other grand challenge of facility
management’s future along with sustainability (Bröchner et al., 2019).
With powerful technologies, great responsibility follows. Ethics of AI
technologies has been recognized as an essential field of research and an integral part
of applying AI. By creating an applied ethical framework, we can ensure both ethically
aligned conduct and efficient and innovative adoption of AI technologies in facility
management. The utilization of AI technologies in facility management does not
necessarily need own ethical principles or guidelines, but applying existing principles
to the field’s challenges and use cases can offer fruitful and strengthened insights for
the debate of applied AI ethics.
Ethics of AI is not an overriding field in ethics but adheres to the tradition of
information technology ethics. Many themes debated might be familiar from the earlier
experiences and ethical implications of digital and information technology, big data,
analytics, and modeling systems. However, ethics of AI forms a vital development of
ethical analysis and thinking, and thus awareness towards the field’s themes and
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons
License Attribution 4.0 International (CC BY 4.0).
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concerns can be crucial for the practitioners and scholars of facility management.
Knowing the topics of ethics of AI can help to form an overall ethical awareness, called
for by Grimshaw, B. (2001).
AI technology can impact facility management’s structure, business logic,
organization, and culture thoroughly. To clarify the starting points of this paper, the
term of facility management refers to the definition by Barrett & Baldry (2003): “an
integrated approach to operating, maintaining, improving and adapting the buildings
and infrastructure of an organization in order to create an environment that strongly
supports the primary objectives of that organization.”
Possible application areas of AI in FM include security robots, control and
surveillance systems, autonomous guidance, catering and cleaning, and intelligent
maintenance applications. (Hoar et al., 2017). Definition of AI is still under debate -
and often challenged by the computer scientists and engineers - but some baseline
specifications of AI will make the societal and ethical discussion more valuable.
The definition of AI by the European High-Level Expert Group is a good
starting point:
“Artificial intelligence (AI) refers to systems that display intelligent behaviour by
analysing their environment and taking actions – with some degree of autonomy – to
achieve specific goals.
AI-based systems can be purely software-based, acting in the virtual world (e.g. voice
assistants, image analysis software, search engines, speech and face recognition
systems) or AI can be embedded in hardware devices (e.g. advanced robots,
autonomous cars, drones or Internet of Things applications).”
The report “Artificial intelligence: What it means for the built environment”
(2017) describes broadly various opportunities that AI technologies provide for facility
management. In addition to the advanced methods in construction modeling and design,
AI can support, boost and change the basic functions of everyday facility management
like catering, cleaning, helpdesk and reception services, security functions, and
maintenance. AI also helps to advance the automation and connect devices and sensors
in smart city and smart buildings solutions.
2 Theoretical background
2.1 Ethical grounds for applying AI
Several ethics report and ethical frameworks has been published about the emerging
AI technologies. To mention a few: IEEE published Ethically Aligned Design (2018);
ACM updated its code of ethics (2018); France (2018), the UK (2018), Canada (2019)
and Finland (2019) published their national report of AI ethics. An important and
encouraging report for this paper, “Ethics guidelines for trustworthy AI” (2019) by the
European Union’s High-Level Expert Group on AI, came out in April, 2019.
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After the formulation of principles and guidelines, even more critical phase is
the following: how to start bringing the guidelines alive and integrating principle-level
conduct to the practice. Ethical assessment and evaluation, ethics by design, and
organization-wide awareness of ethical issues related to AI technologies become the
key issues. The humble but profound goal of this paper is to bring a first few thoughts
and ideas about those key issues to the discipline of facility management.
AI is a general-purpose technological change, and it will dramatically affect
most industries. When approaching industry-specific ethical alignment, the first step
could be the transformation of general and high-level guidelines to suit the industry-
specific requirements. For the level of ethical alignment in AI solutions, an example
can be found from the earlier sustainability thinking. Alexander and Brown (2006)
present in their paper five levels for sustainability: compliant, environmentally aware,
balanced performance, socially responsible and corporate citizen. Just by replacing
“environmentally aware” with “aware of ICT and AI ethics”, a preliminary
measurement scale can be proposed.
2.2 Applying “Ethics guidelines for trustworthy AI” to AI in facility
management
As Michael May (2018) states, the sector of facility management should acquire
necessary skills to utilize AI technologies, but at the same time remember the ethical
concerns and questions related to AI solutions. There is a strong tradition of ethical
conduct and guidelines in facility management, and similar approach should be applied
to the AI technology from the beginning.
The European Guidelines for Trustworthy Artificial Intelligence offers a good
opportunity to adapt the presented ethical principles and requirements into more
practical sector. While the research literature bursts over with the overall level
principles of ethical AI, industry-specific application and conceptualization of these
principles should be greeted with joy.
The European High Level Expert Group’s report “Ethical Guidelines for
Trustworthy AI” describes seven high-level principles and ethical categories as the key
requirements of ethical AI. Writing these principles open and reflecting them to the
field of facility management, it is possible to find key remarks and control points for
ensuring ethical AI in facility management. The following key points from the report
seem to be important to ask and analyze also when it comes to facility management:
Human agency and oversight
AI solutions should promote fundamental rights and support human autonomy. AI
technologies offer powerful tools for the implementor, and their use should be assessed
and monitored to minimize the possibility of misuse, e.g. violating the right to privacy
or discrimating based on age or gender, abilities or characteristics when it is not
justified. Another essential point is to ensure human oversight: although the autonomy
level of AI solutions rises, we must ensure the capability for human intervention and
control of all the AI systems.
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Technical robustness and safety
To some extent, we have to rely on it that technology vendors pursue technical
robustness, but buyer-side evaluation is necessary as well. What is the skill set needed
for evaluation of technical robustness and safety? Do the facility management
community and facility managers have enough knowledge, insight and experience for
the evaluation? We need to ensure that they do or can find suitable people to do so.
Privacy and data governance
Technological development during the past decades has challenged our right to
privacy. The implementors of technology solutions are extensively capable of
collecting data about us. AI technologies increase these capabilities and reinforce the
ability to build a wide range of applications on top of the collected data. Defending
privacy can easily conflict with other purposes: As described by Bröchner et al. (2019),
privacy and personal integrity might clash with e.g. other themes of sustainability, like
environmental development for lowering energy consumption based on data-heavy
analysis. These situations require careful analysis and decision-making.
Transparency
Transparency includes traceability, explainability and strong call for
communication. How to enable transparent conduct to all technology solutions? How
to use co-creation to involve all the stakeholders? Transparency has been recognized as
an essential principle in various ethical guidelines and codes, but in practice, achieving
transparent organization culture and practices seems difficult. Are your organization’s
facility managers prepared to be transparent in the planning and implementation of AI
solutions? And most importantly, are they prepared to be transparent if the AI solutions
fail?
Diversity, non-discrimination and fairness
AI technologies make some of our societies’ biases and injustices visible, and AI
solutions should be monitored against discriminating effects. For example, facial and
object recognition systems might recognize white male persons better than anyone else
(Buolamwini & Gebru, 2018), as the makers and internal test subjects have mostly been
white males. Also accessibility design appears essential: when implementing
autonomous and complex AI systems for helpdesk, access control or catering, the needs
of different people and groups have to be taken into account as comprehensively as
possible.
Societal and environmental wellbeing
AI solutions should promote societal and environmental wellbeing. How is facility
management answering to the societal challenges of AI technologies? How to optimize
workplaces to human-robot-interaction? Virtual and augmented reality offers
efficiency for meeting and face-to-face collaboration, but how to ensure socially viable
environment for work and life?
Accountability
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Who will be responsible and accountable? For a data breach? Security failures or
safety issues? Mistakes in access control or recognition systems discrimating certain
population groups? Accountability and responsibility should be negotiated and agreed
clearly in every AI implementation. Accountability should be communicated clearly,
and responsibility should be real, not vanishing under bureaucracy.
3 Plan for empirical research
Empirical interview research will follow this conceptual paper. The empirical research
consists semi-structured interviews with three to five leading Finnish facility or real
estate managers with knowledge and ability to answer technology-related questions
about their field. The brief empirical research will be conducted during the autumn
2020.
The empirical part of the study targets to answer the following questions:
Which AI systems or applications are used in the facility management sector now and
in 3-5 years? How well the conceptualizations presented in this paper land to describe
the possible ethical challenges of applying AI in facility and real estate management?
What could the concrete form and the intended use of the ethical framework an ethical
framework for applying artificial intelligence in facility management?
4 Discussion
We are still in the phase where the facility management community sorts out and plans
how and where to utilize AI solutions. Ethics must emerge alongside these concerns
from the beginning, and industry-specific ethical guidelines should be defined and
agreed together with the community so that ethical concerns are solved with the
introduction of the technology, rather than added as a band-aid after implementation.
Strong ethical alignment will likely result in the most valuable, societally viable and
long-lasting achievements.
In the AI ethics community, we are moving to analyze and solve how to
integrate the ethical guidelines as well as possible to the practices in the more specific
industries affected by AI. Technology industry should carry a strong responsibility for
the emerging technologies, but other industries should follow the ethical conduct when
integrating AI technology to their everyday solutions. This paper functions as a start of
the debate and analysis.
Ethics of AI is not about mystical fear-mongering, but about the challenging
transformation affecting most industries. Awareness about the themes and concerns of
AI ethics helps to integrate ethical thinking to the existing models of handling
innovation, change and professional conduct. Innovation, change and professionality
are core themes for facility management, and aligning AI ethics to the themes and the
discipline itself is compulsory.
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5 References
ACM Code of Ethics and Professional Conduct (2018). ,
retrieved 11.2.2019.
Alexander, Keith – Brown, Martin (2006) "Community‐based facilities management", Facilities,
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Atkin, B. – Brooks, A. (2015). Total facility management. John Wiley & Sons.
Barrett, P.S. – Baldry, D. (2003) Facilities Management: Towards Best Practice, 2nd edn.
Blackwell, Oxford.
Bie, Svend (2018) Digitalization: Double challenge and double possibility to facility
management. eFMi Issue 47 Dec 2018 / Jan 2019.
Bröchner, Jan – Haugen, Tore – Lindkvist, Carmel (2019) "Shaping tomorrow’s facilities
management", Facilities, Vol. 37 Issue: 7/8, pp.366-380, https://doi.org/10.1108/F-10-
2018-0126.
Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in
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Grimshaw, B. (2001). Ethical issues and agendas. Facilities, 19(1/2), 43-51.
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IEEE: Ethically Aligned Design, version 2 (2018) , re-trieved
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May, Michael (2018) Artificial Intelligence and Machine Learning in FM. eFMI Issue 45, June
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