Legal Design is inspired by the concepts of Design Thinking and User Experience: the ultimate goal is to make citizens more aware with well-designed rules and procedures in terms of 'Proactive law', providing policies that are truly user-centered, tailored to the cognitive needs both expressed and hidden through continuous and transparent communication. Talking about privacy, there is a clear need, starting from the analysis of the texts of some documents (e.g.'information on the use of personal data' and 'consent'), to translate 'bureaucratic' requests into simpler questions, as to allow the more intuitive, usable and inclusive user experience. So, in the wake of the GDPR view too, we have been experimenting how the advantages of communicating and involving the citizens by design and by default can prove to be the right key so that the privacy documents they encounter in the everyday life can finally transmit transparency and a sense of control of the situation that are both much more substantial and immediately perceptible. The future developments of the project will be focused on enhancing access to safeguards for digital privacy, as well as citizens' awareness of their digital rights, a fortiori for the weakest subjects, with a chatbot providing personalized educational/assistance services. In the final stage I will be concepting a prototype of such an educational chatbot ranging between rights to be deployed, user experience to be exalted and training effectiveness to be ensured.
Everyday people, both as individuals and families and as businesses, are forced to interface with
contracts, documents and legal procedures often without having the appropriate skills to “navigate”
these systems. In many countries, the difficulty of bureaucracy and legal language often puts citizens
in difficulty, causing a sense of inadequacy towards the legal system but also the feeling of not having
full control of their situation
So, some researchers have been discussing how the legal system could be rethought in terms of
language and tools through the design approach. The discipline that tries to answer this question has
been called “Legal Design”
In general terms, Legal Design is inspired with the concepts of Design Thinking and User
Experience (UX)
Not only does a graphic and visual form made more effective in terms of Visual Law1 help to understand the content of a privacy document, but it can also help the understanding of the related legal process.
In essence, the goal is to make citizens more aware with well designed rules and procedures in
terms of ‘Legal Design’, also towards the production of documents – just like in the Privacy’s field2
that are simple, clear, attractive to the recipients
My project aims at improving the information addressed to individuals in the procedures for
accessing legal protections on privacy through the redesign of formulas, forms, graphic interfaces and
the construction of an educational chatbot that provides for a dynamic interaction with the user in a
solution-oriented manner
So the ultimate goal of this project is to design and develop an educational chatbot who can help the user to fully understand the privacy policy when entering a website. By teaching what are his/her rights and how they can be effectively deployed, the chatbot will act as a trainer, too.
In the creative society, consumers not only receive products or services and engage with the
providers via feedback and customised requirements but also generate the solutions to their own needs
The environment of the creative society will not only allow its design but will solicit from groups
and individuals in constant redesign cycles (creation): for instance, legal hackathon formats or legal
design workshops constitute sparks of what in the future will be widespread and commonplace in the
Creative Legal society
Under the new paradigm of the creative society, the capability to ‘create’ will no longer be exclusive of corporations but available to teams of individuals and communities.
In the last years, Legal Design has emerged pushing from the periphery to the centre of the legal
system introducing concepts like human-centeredness, creativity, visualisation in legal
communications. In the spirit of setting a space for a metatheory for Legal Design as an academic
discipline, some authors (Santuber, Owoyele, Krawietz, Edelman, cit.) proposed four theories from
which they could leverage: (i) autopoietic systems
Operationally, Legal Design is characterised as a network that articulates the coupling of the autopoietic systems. The constructs are (a) human being, (b) creative process and (c) Law, so Legal Design is materialised in the interaction of constructs (Fig. 2). While the formalities of a legal system restrain communication within the same, thus depriving it of creative opportunities, networks can be described as continual, communicative relationships of exchange, characterised by informality, innovative power and the ability to self-organise.
Therefore, the practice of Legal Design requires a media to facilitate the interaction between the human being, the creative process and the Law, so that: a) These media are models and frameworks, deployed in concrete tools for the practice of Legal
Design. b) The structural coupling emerges as a perception-action cycle. In this loop, the perception of one system from another system occurs, because the latter is acting on the first.
In this scheme, the human being perceives the legal system and acts on the creative process as a contributor. The creative process perceives it and acts on the legal system. The legal system perceives it and act on the human being who originally perceived the legal system. Each cycle implies an adaption and reorganization of each one of the constructs”.
Do people appreciate the prospects of Legal Design applied to Privacy documents, also in the light 4 of the innovations introduced by the GDPR ?
Citizens perceive the need to simplify the visualization5 and will appreciate the potential of legal design from the simplification of language, to the redesign of privacy documents, up to the simplification of procedures both for citizens and for professionals and operators6.
The key point, starting from the analysis of the texts of some modules (e.g. ‘information on the use of personal data’ and ‘privacy consent’ for various activities), is to “translate” the requests - almost always perceived both by the writers and by the users as bureaucratic or slightly more - in simpler questions, also adapting to the level of understanding of the user’s language.
The benefits in terms of accessibility to be reached are: – firstly in respect of parameters such as the effectiveness of the personal data protection in all its lifecycle (Fig.3),
– above all ‘active’, that is, thanks to which, people are put in a real condition to know thoroughly their rights and to be able to exercise them in practice as effectively as required by the regulations.
Often conversation about privacy communication design gets caught in a debate about
oversimplification versus overcomplication. What’s emerging is discussion of a ‘third way’ (Fig. 4),
that is focused not on simplification but engaging user experiences – that are more focused on
people’s contexts, problems, and questions
With this in mind, our 'Let’s Draw the Privacy of the Future' initiative participated with great success in the XXXIII edition of “Futuro Remoto, Essere 4.0”, held in Naples at ‘Città della Scienza’. For the first time in Italy7, a team of professionals and experts has provided to interactively illustrate examples of privacy documents with the aim of highlighting all the texts and expressions that the ordinary citizen may find difficult to understand. "Prototypes" of redesigned documents were then shown, using visual techniques, enriched with illustrations, diagrams and icons more intuitive for the
The great success of the initiative has given the opportunity to highlight how the new design is not only graphic but reduces the information to be communicated and the vehicles to the essential in an intuitive and immediate way so as not to discourage, indeed favour the reading and understanding of their rights and how to exercise them in practice.
Here is the questionnaire administered to the participants (Fig. 5). 7 At that moment, we knew only one scientific experiment carried out: “Our exploratory interviews involved a small sample size of around 20 people, with whom we spoke for ten to twenty minutes in person. These in-depth discussions revealed several central insights into how young, technology-literate people interact with privacy policies. We then examined these insights with our online survey, which confirmed two key findings: users have a wide variety of privacy concerns that are not clearly prioritized or universal among all users in our chosen persona type; and that these concerns do not translate into engagement with a privacy policy document on their phone, inside apps, or on technology companies’ websites”, as reported in Margaret Hagan, User-Centered Privacy Communication Design, Stanford Law School/d.school, Symposium on Usable Privacy and Security (SOUPS) 2016, June 22-24, 2016, Denver, Colorado. Page 3. URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2981075. 8 For more details see Sergio Guida, Legal Design & Visual Law: prospettive in Italia anche alla luce delle novità introdotte dal GDPR, Data Protection Law.it, ISSN 2611-6456, February 6, 2020. URL: https://www.dataprotectionlaw.it/2020/02/06/legal-design-visual-lawgdpr/. Yes Neither Yes nor No
The results of the interviews (for a total of 136), as well as their feedback, comments, ideas, suggestions, will be detailed in a further research. At the moment, I can indicate the main aggregate results (Fig. 6).
Lessons learned
1. Multidisciplinary skills are very important in the design and implementation of highly
innovative products and services based on legal design, aimed at maximizing user experience
2. Particular attention has to be given to ‘weak subjects’, for whom, in addition to the fundamental objective of allowing full accessibility and usability of privacy rights, the highest objective would be to bring out and enhance the enormous patrimony in terms of Human Capital (Botev et al., OECD, 2019) which more often in their case lies latent and unexpressed.
3. Policies simplification of access to legal protections in order to make them effective and to increase the trust of users in the processing of data which, in any case, have a significant impact on the individual’s fundamental rights.
4. Clarity and simplification are also fundamental in contractual relationships between private individuals and for access to goods and services, in order to reduce obstacles to understanding procedures and processes and within the framework of a renewed relationship of trust between citizens and with institutions.
On the basis of these results it will be possible to improve the effectiveness of existing privacy regulations and to enhance access to safeguards, e.g. through a chatbot (and eventually personalized assistance services) ranging between rights, user experience and educational issues9. 9 Cf. “Educational or learning goals are inspired by a specific learning theory, such as the already cited work by Bloom or Kolb who emphasized concrete experience, active experimentation, reflective observation, and abstract conceptualization. A meaningful learning process is characterized by the presence of feedback, as giving (and receiving) feedback is essential to understand how close learners are to the defined learning goals. Feedback, together with debriefing are regarded as the most important element for maximizing the learning process, as they guide learners through a reflective process about their learning, offer a space for giving personal meaning to the learning experience, and help to relate this learning experience to real-life contexts”, as we can read in Michela Ponticorvo, Elena Dell'Aquila, Davide Marocco, Orazio Miglino, Situated Psychological Agents: A Methodology for Educational Games, Applied Sciences 9(22):4887 November 2019, DOI:10.3390/app9224887, page 7. URL: https://www.researchgate.net/publication/337268184_Situated_Psychological _Agents_A_Methodology_for_Educational_Games.
Chatbots have had a long history of use as pedagogical agents in educational settings. From the early 1970s, pedagogical agents within digital learning environments known as Intelligent Tutoring Systems have been developed (Laurillard, 2013). Conversational pedagogical agents use artificial intelligence techniques to enhance and personalize automation in teaching. The design and research knowledge are important in developing engaging, useful, and valuable pedagogical agents that not only make the most of technological advancements, but also understand emotional, cognitive, and social educational concerns (Gulz, Haake, Silvervarg, Sjoden, & Veletsianos, 2011). In addition, conversational agents have been built into software and devices. Useful chatbot systems can provide benefits of instant availability and ability to respond naturally through a conversational interface with the same advantages as an interview. Additionally, chatbots demonstrate the ability to create easygoing interactions with users so that they can be leveraged to support engagement, as well as setting out goals, strategies and outcomes of learning and training (Pappas, 2014).
So the time has come to schematically consider the ‘Structural properties’ of the ‘stage’10 where the intervention setting takes place (Chimera, Baim, 2010), as described in Figure 7.
suggestions of the chatbot-educator by changing the structure of the educational materials.
Person in the periphery of the setting: a woman learns by observing the actions of the girl interacting with the chatbot, she can influence the girl's
action with her comments, she cannot change the structure of the educational
materials.
between people, tools can be physical (such as the PC) and abstract (such as language and facial and postural expressions).
10 The analogy between a setting of psychological intervention and the techniques of the “commedia dell’arte” was already developed by the famous psycho-sociologist Jacob Moreno who used it in psychosocial intervention techniques called ‘psycho-drama’, as extensively explained in the slides of our Master’s course "Artificial Intelligence Systems and Technologies for Psychology Interventions". In Figures 7 and 8 I made my own elaborations starting from a similar scene contained in an example provided in the Lessons of the Course, while in Figure 9 I inserted a translation of the original slides.
As regards ‘Functional properties’, the canvas defines the roles of the characters who enter the scene (on stage) in a very similar way to the definition of protocols and guidelines contemplated in the definition of a psychological intervention setting.
Figure 8 depicts an example of developing a flow chart of a Psychodrama session (or role-playing game) applied in the context described in the previous figure 7: the boxes show very general macroactivities but useful to distinguish the various phases in which the role play takes place. Some sections of this quasi-formalism will be expressed in formal terms and represent the basis for developing our projected chatbot.
The user intends to connect to an e-commerce website together with a friend to ask for advice on the purchase to be made and defines the maximum time (T max )in which the" negotiation "must be concluded. The girl does not want to give a 'pro-forma' consent to the processing of her data, but she wants to understand well the implications of each choice on the exercise of her rights, with the help of the chatbot-educator.
The simulation (representation)
ends Participants move on to the debriefing phase.
Thosedirectly involved in the psychological intervention (the actors)simulate (orrepresent in a theatrical form) the negotiation.
Yes t = T ma x No No
Yes Is the chatbot-trainer required to intervene in any form? The chatbot-trainer carries out his intervention.
Figure 9 presents the two phases in which we can describe the path that goes from the almost intuitive conception of some technological support to be included in a given setting of psychological intervention to its implementation and use.
In figure 9 Phase a (design and implementation of a technology) is divided into three distinct steps, while Phase b (release, use and evaluation of the insertion of the technological support) is presented as a single body.
The first step of Phase a will be dedicated in the first instance to the qualitative description of the structural properties of the psychological intervention setting, also using graphic representations (such as shown in previous figures) and to the qualitative definition and intuitive of the functional properties of the setting also through a diagram of non-algortimic flows as presented before.
The second step of phase (a) involves the detailed and formal design of the structural and functional components of the setting that you want to enhance / replace with the technology we are going to develop (educational chatbot). In this step, for example, it will be necessary to develop an algorithmic flow diagram of the functional properties of the setting that is to be transformed into the concrete technology.
In the third step it will be necessary to choose the IT tools (programming languages) and hardware (computer) necessary for the realization of the previously designed technological solutions. Generally, before reaching the final stabilization of a project, several iterative cycles are required between the activities of step 2 and step 3.
PhaseA-Conception,designanddevelopmentofatechnologytosupportinterventionsinPsychology
accordingtotheSPAFmethodology
Step 2: Technology design: design in computer and / or mathematical terms of the various components (agents or tools) of a setting that you want to enhance / replace with a technology.
Step3: Implementation: Softwareandhardwaredevelopmentofthetechnology(s)to be introducedinagiven psychologicalinterventionsetting.
Phase B - Release and evaluation of the technology at
various levels of analysis Verification of the efficiency and effectiveness of the technological solution:ergonomic analysis, evaluation of the achievement of psychological objectives, ethical analysis, economic evaluation, etc.
Chatbots use a dialogue system to have a conversation with a human. There are a few steps a chatbot goes through to process human information:
The first step is converting human input into an understandable context for the chatbot. This is done through input recognizers and decoders, which can analyze speech, text and even gestures.
The next step is applying Natural Language Processing (NLP) to analyze the plain text and search for semantics (Callahan, 2021). After the tasks are solved the output manager translates the solution into ‘human like output’.
However, these natural responses require a great amount of learning time and data to be able to learn the vast amount of possible inputs. The training will prove if the bots are able to handle the more challenging issues that are normally posed by users, just like in our field survey.
The prototype of my educational chatbot, as so far only imagined, will have the strategic goals of finding the right balance between the different needs to be reconciled, namely rights to be protected, user experience to be maximized and training that is truly effective for the user's growth, also and above all as a citizen.
I would like to thank hugely our Master’s Teachers for inspiring my work.
This Word template was created by Aleksandr Ometov, TAU, Finland. The template is made available under a Creative Commons License Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).
[19] J. Botev, B. Égert, Z. Smidova, D. Turner, A new macroeconomic measure of human capital with strong empirical links to productivity, OECD Economics Department Working Papers, No. 1575 - 2019. URL: https://doi.org/10.1787/d12d7305-en. [20] M. Ponticorvo, E. Dell'Aquila, D. Marocco, O. Miglino, Situated Psychological Agents: A Methodology for Educational Games, Applied Sciences 9(22):4887 November 2019, DOI:10.3390/app9224887. URL: https://www.researchgate.net/publication/337268184_Situated_ Psychological_Agents_A_Methodology_for_Educational_Games. [21] D. Laurillard, Rethinking university teaching: A conversational framework for the effective use of learning technologies, Routledge, London, UK (2013). URL: https://doi.org/ 10.4324/9780203160329. [22] A. Gulz, M. Haake, A. Silvervarg, B. Sjödén, G. Veletsianos, Building a social conversational pedagogical agent: Design challenges and methodological approaches, IGI Global, Hershey (2011), 10.4018/978-1-60960-617-6.ch006, URL: https://citeseerx.ist.psu.edu/viewdoc/download ?doi=10.1.1.396.7984&rep=rep1&type=pdf. [23] C. Pappas, Instructional Design Models and Theories: The Generative Learning Theory,
November 16, 2014. URL: https://elearningindustry.com/generative-learning-theory. [24] C. Chimera, C. Baim, Introduction to Psychodrama, Workshop for IASA Conference, Cambridge, 29th August 2010. URL: https://www.iasa-dmm.org/images/uploads/Chip%20 Chimera%20and%20Clark%20Baim%20Workshop%20on%20Psychodrama.pdf. [25] G. Callahan, Natural Language Processing Technology Explained, Rev.Ai, June 23, 2021. URL: https://www.rev.ai/blog/what-is-natural-language-processing-technology/.