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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Mapping policymakers' and laypeople's perceptions of genAI and FPT</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Chiara Ullstein</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Michel Hohendanner</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Jens Grossklags</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>EWAF'24: European Workshop on Algorithmic Fairness</institution>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>HM Hochschule München University of Applied Sciences, Munich Center for Digital Sciences and AI</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Technical University of Munich, Chair of Cyber Trust</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>The recently enforced EU AI Act has advanced the state of AI regulation and is largely perceived as a valuable step toward regulating AI. Nevertheless, some articles of the AI Act remain contested and raise societal concerns, highlighting that the AI Act's aim to support the development of trustworthy AI is a continuous endeavor, also in terms of discourse with society. Two highly discussed AI application areas with great impact on societies worldwide are facial processing technologies (FPT) and generative AI (genAI). For a socially sustainable regulatory approach, discourse between policymakers and citizens is important. This requires, on the one side, understanding policymakers' general opinions on citizen participation. On the other side, there is the need to know which touchpoints and perceptions laypeople worldwide currently have with and about these AI application areas. To learn about the perceptions of both target groups, we surveyed policymakers and experts (N = 61) and laypeople (N = 1070) worldwide in late 2023. Combining these two exploratory survey studies allowed us to identify key topics that are relevant to policymakers and citizens to inform policy processes in light of the EU AI Act and beyond. In the context of a larger research project, the results serve as a foundation for designing a citizen deliberation process on FPT and genAI across continents. In this short paper, we motivate and contextualize our research, present our research approach, and describe the first results.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;facial processing technologies</kwd>
        <kwd>generative AI</kwd>
        <kwd>public perception</kwd>
        <kwd>EU AI Act</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        1. Introduction
“There are more questions than answers about how this technology will shape our environments
and interactions, and policy is struggling to keep up with developments” [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. This assessment of
generative AI (genAI) in a recent OECD report [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ] highlights the technology’s broad impact and
the need for research to guide policymaking. Also intensively debated is the impact of facial
processing technologies (FPT). Throughout the EU AI Act development phase, initiatives [e.g.,
2, 3] pointed out risks such as being biased, or violating basic rights, and campaigned for the
ban of facial recognition technologies (FRT). Others argued for safety benefits [e.g., 4].
      </p>
      <p>Strong and partially competing interests by diferent stakeholders emphasize that at the
core of sustainable regulatory approaches should be a continuous review of global societal
perceptions of technologies. These can serve EU policymaking as important (warning) signals
concerning regulatory blind spots, and explain how and why technology is (not) accepted or
adopted. In light of the regulatory legitimization of certain FPT use cases and the rapid roll-out
of genAI into various domains, laypeople’s perceptions should be steadily studied as they are
primarily afected by the adoption of these technologies. As such, spaces for discourse, as well
as ongoing alignment checks of the interests of policymakers and citizens’ needs, are crucial.</p>
      <p>In this short paper, we present the design and initial results of two exploratory survey
studies laying the groundwork for a citizen deliberation research project on genAI and FPT by
identifying key topics that are relevant to citizens and policymakers. With this project, we aim
to provide critical input for policymaking and the implementation of the EU AI Act.</p>
    </sec>
    <sec id="sec-2">
      <title>2. Recent Discourse and Related Work</title>
      <p>
        The abrupt rise of genAI has spurred extensive public discourse, prompting the publication
of an open letter in March 2023 to pause giant AI experiments to “give society a chance to
adapt” [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. Governments and organizations, such as the OECD, released policy considerations in
September 2023 [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], the G7 published the “Hiroshima Process International Guiding Principles
for Advanced AI system” [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ] in October 2023, and the European Parliament and the Council
agreed upon the regulation of genAI through the EU AI Act in December 2023 [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ], enforced
in August 2024 [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ]. Concerning FPT, the EU AI Act bans biometric categorization systems
that use sensitive characteristics, untargeted scraping of facial images from the internet or
CCTV footage, emotion recognition in work and educational contexts, and facial recognition in
public spaces by law enforcement with exceptions [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]. Applications considered high-risk and
requiring conformity assessment include facial recognition as a safety component of products,
and all unprohibited biometric identification, biometric categorization, and emotion recognition
systems [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]. Nevertheless, there has also been continued criticism [
        <xref ref-type="bibr" rid="ref10 ref11">10, 11</xref>
        ].
      </p>
      <p>
        Prior work on potential benefits of genAI stated that ChatGPT can enhance customer service,
automate repetitive tasks, enable 24/7 accessibility, aid educators and students, and serve as
information and accountability tool within institutions [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ]. Others highlight opportunities
and threats across sectors and for culture and leisure [13]. For text-generating genAI, raised
concerns include bias, negative impact on democratic processes, generation of false information
and associated privacy concerns, and risk of job loss [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ]. For text-to-image systems, further
potential risks include discrimination and exclusion, misuse, and mis-/disinformation [14]. Prior
work on public perceptions of genAI analyzing Twitter data found a generally positive sentiment
across occupations, which correlates with exposure to AI [15]. Likewise, IT practitioners in the
public sector indicated a high interest in and are optimistic about genAI, but are also concerned
about emerging threats [16]. Raised concerns regarding the unethical use of artworks for
training data played a major role in the negative sentiments of illustrators [15].
      </p>
      <p>Prior work on FPT shows that particularly FRT exhibits bias, leading to a performance
decline on facial data from children [17], women, and people of color [18], thereby reinforcing
“existing racial disparities” [19]. To assess risks, researchers advocate for, e.g., a Human Rights
Impact Assessment and regular audits [20]. Prior work finds that public perceptions vary with
the FRT application context [21]. Influencing factors include the control over facial data, the
trustworthiness of the organization deploying FRT, the utility of FRT, and the surroundings
and location of FRT use [21]. Participants weighed the security, usability, and economic gain of
FRT with privacy risks [21]. We use these research findings and recent policy discussions as a
foundation for our surveys to cross-nationally compare views on genAI and FPT.</p>
    </sec>
    <sec id="sec-3">
      <title>3. Method</title>
      <p>Policymakers and experts survey (S1). Data collection: In November and December 2023,
we first surveyed policymakers and experts by sending out a total of 652 survey invitations. We
received 61 responses from across the world. Survey: We asked policymakers and experts what
topic (referring to genAI and FPT) they would like to hear citizens’ opinions on, how relevant
genAI and FPT are to their work, how knowledgeable they are, and how they perceive citizen
participation. We concluded with closed questions describing their current role. The mean
duration was 8.22 minutes. Participants: Respondents had 37 diferent nationalities, max. 3
participants from the same country (9 did not indicate). 20 respondents indicated to be female,
41 to be male. 3 participants stated to work at the European Parliament, 4 at the Council of
Europe, 2 at the OECD, 27 at a national government, and 25 in academia, a research center, an
NGO, or a private institution related to AI. Limitations: Due to the relatively low number of
participants, frequency analyses should be interpreted with caution.</p>
      <p>Citizen survey (S2). Data collection: In December 2023, we surveyed English-speaking
laypeople across twelve countries and five continents via Prolific. The final dataset covers 1070
participants. Survey: Participants were randomly either drawn into the genAI or FPT technology
context, where basic information on either genAI or FPT was provided. We then asked about
perceived risks and benefits (open questions), and explored their opinions concerning several
touchpoints with and trade-ofs for specific use cases (closed questions). The trade-ofs and
use cases were selected based on prior research and policy discussions [e.g., 14, 22, 23, 24] and
provided to participants in an informative manner, enabling them to learn and develop opinions
about the technology in diferent contexts. Aligned with the EU AI Act, the FPT use cases
covered high-risk and limited-risk AI systems. Finally, we asked about measures for safe and
ethical technology use (open question) and who should introduce such measures or regulate
the technology (closed question). The mean survey duration was 22.55 minutes. Participants:
Participants’ nationalities are Nigerian (N=110), South African (N=105), Indian (N=96), Japanese
(N=24), South Korean (N=31), German (N=105), British (N=109), American (N=117), Canadian
(N=106), Chilean (N=100), Mexican, (N=104), Brazilian (N=63). 526 respondents indicated to be
female, 523 to be male, 14 to be non-binary, and 7 preferred not to say. Limitations: Participants
self-selected via Prolific, potentially impacting generalizability. To counter potential biases,
gender balance was ensured. The survey was rolled out in English, possibly attracting more
higher-educated individuals.</p>
      <p>Data analysis. S1: We applied manual content analysis [25, 26] to the open-text responses.
S2: We performed automated topic modeling [27] refined by manual re-clustering on the
opentext responses. S1/S2: We applied frequency analysis to multiple-choice and scale questions.</p>
    </sec>
    <sec id="sec-4">
      <title>4. First Results and Final Remarks</title>
      <p>In the first survey (S1), we find that the majority of policymakers and experts perceive genAI and
FPT to be (somewhat) relevant to their fields. They generally perceive citizen participation to be
valuable: 84% perceive citizen participation to “strengthen democratic institutions.” While 80%
think that citizen participation might give voices to those less frequently heard, 70% indicated
that they may be able to learn from the public’s opinions or judgments. Participants would
like to hear citizens’ opinions about the areas of regulation (what, who, how), perception of
application contexts (individual use, public service, business contexts), awareness and
informedness (technical knowledge, awareness, education, trust), and trade-ofs and concerns (individual
harms, transparency and accuracy, misuse, data security and protection).</p>
      <p>In our second survey (S2), for both technologies, participants trust international institutions
run by experts the most to establish measures that make the use of genAI and FPT safe. They
believe that companies developing the technologies or those using the technologies, and for FPT
also the government, should be held accountable if the technology leads to harmful outcomes.
Participants indicate to have been most exposed to text-generating genAI use cases and least to
audio genAI. The awareness of perceived exposure varies significantly for the presented FPT
use cases, with participants being most aware of FPT for unlocking devices or verification at
airports, and least with emotion recognition in work or educational contexts. When confronted
with specific scenarios, participants across all countries find misinformation through genAI
and misuse of facial data for FPT to pose great harm. Opinions are most diverse regarding the
benefits and harms of genAI in the arts and the benefits of FPT for societal security. Participants
perceive a value of genAI in the field of education and for increased personal eficiency in the
workplace. At the end of the survey, participants reported being less excited and more nervous
than at the beginning – an efect stronger for participants in the FPT context.</p>
      <p>Comparing results from both surveys (S1 and S2), discussed topics with greater shared interest
between experts and laypeople emerge: the need for regulation and specific regulatory strategies
to ensure data security, privacy, and transparency. Also, assessing risks, benefits, and the overall
impact on society, the job market and education are shared topics. Furthermore, ethical concerns
stemming from dis-/misinformation and consequences of potential bias, and the need for raising
awareness and educating laypeople are mentioned. One topic missing in citizens’ responses
but being of greater interest to experts is the use of genAI in public administration. Topics that
are frequently mentioned by laypeople but rarely by experts are general misuse (aside from
dis-/misinformation) and the need for responsibility and accountability for ethical use.</p>
      <p>These initial results point to topics that are perceived by policymakers and citizens as subject
to discussion. Other topics crystallize as being of exclusive interest to policymakers or citizens.
We further analyze the data regarding national-specific diferences in perception [ 28]. The
results of this research project can help experts and policymakers to direct their attention
to the issues that laypeople worldwide perceive to be most central, striving for technology
development, deployment, and application in a trustworthy manner. We take these exploratory
results as a basis for designing citizen deliberations on genAI and FPT taking place across
multiple continents. Methodologically, these deliberations will also be informed by our previous
work [29, 30, 31, 24]. We hope this project will fruitfully enhance the public discourse and
contribute to a continuous exchange between the policy, academic, and citizen spheres.</p>
    </sec>
    <sec id="sec-5">
      <title>Acknowledgments</title>
      <p>We are thankful for the contributions of all the participants who took part in our studies. We
sincerely thank Nikhil Sharma, Simeon Ivanov, and Georgi Tsipov for their assistance with this
research project. We gratefully acknowledge partial support from the Institute for Ethics in
Artificial Intelligence (IEAI) at the Technical University of Munich. The citizen deliberations,
taking place in 2024, will be co-financed by the IEEE Computer Society through the Emerging
Tech Grants Program.
[13] A. Bahrini, M. Khamoshifar, H. Abbasimehr, R. J. Riggs, M. Esmaeili, R. M. Majdabadkohne,
M. Pasehvar, ChatGPT: Applications, opportunities, and threats, in: 2023 Systems and
Information Engineering Design Symposium (SIEDS), IEEE, 2023, pp. 274–279. doi:10.
1109/SIEDS58326.2023.10137850.
[14] C. Bird, E. Ungless, A. Kasirzadeh, Typology of risks of generative text-to-image models,
in: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (AIES),
ACM, 2023, pp. 396–410. doi:10.1145/3600211.3604722.
[15] K. Miyazaki, T. Murayama, T. Uchiba, J. An, H. Kwak, Public perception of generative AI
on Twitter: An empirical study based on occupation and usage, EPJ Data Science 13 (2024).
doi:10.1140/epjds/s13688-023-00445-y.
[16] L. Z. Knutsen, J. David Patón-Romero, J. E. Hannay, S. S. Tanilkan, A survey on the
perception of opportunities and limitations of generative AI in the public sector, in: World
Conference on Information Systems for Business Management, Springer, 2023, pp. 503–520.
doi:10.1007/978-981-99-8349-0_40.
[17] N. Srinivas, K. Ricanek, D. Michalski, D. S. Bolme, M. King, Face recognition algorithm
bias: Performance diferences on images of children and adults, in: Proceedings of the
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019, pp.
2269–2277. doi:10.1109/CVPRW.2019.00280.
[18] J. Buolamwini, T. Gebru, Gender shades: Intersectional accuracy disparities in commercial
gender classification, in: Proceedings of the 1st Conference on Fairness, Accountability
and Transparency, volume 81, PMLR, 2018, pp. 77–91. URL: https://proceedings.mlr.press/
v81/buolamwini18a.html.
[19] F. Bacchini, L. Lorusso, Race, again: How face recognition technology reinforces racial
discrimination, Journal of Information, Communication and Ethics in Society 17 (2019)
321–335. doi:10.1108/JICES-05-2018-0050.
[20] D. Almeida, K. Shmarko, E. Lomas, The ethics of facial recognition technologies,
surveillance, and accountability in an age of artificial intelligence: A comparative
analysis of US, EU, and UK regulatory frameworks, AI and Ethics 2 (2022) 377–387.
doi:10.1007/s43681-021-00077-w.
[21] S. Seng, M. N. Al-Ameen, M. Wright, A first look into users’ perceptions of facial recognition
in the physical world, Computers &amp; Security 105 (2021) 102227. doi:10.1016/j.cose.
2021.102227.
[22] J. Shi, R. Jain, H. Doh, R. Suzuki, K. Ramani, An HCI-centric survey and taxonomy of
Human-Generative-AI interactions, arXiv Working Paper 2310.07127, 2023. doi:10.48550/
arXiv.2310.07127.
[23] J. Buolamwini, V. Ordóñez, J. Morgenstern, E. Learned-Miller, Facial
recognition technologies: A primer, 2020. URL: https://circls.org/primers/
facial-recognition-technologies-a-primer.
[24] C. Ullstein, J. Pfeifer, M. Hohendanner, J. Grossklags, Mapping the stakeholder debate
on facial recognition technologies: Review and stakeholder workshop, in: Companion
Publication of the 2024 Conference on Computer Supported Cooperative Work and Social
Computing (CSCW), ACM, 2024. doi:10.1145/3678884.3681887.
[25] P. Mayring, Qualitative content analysis: Theoretical foundation, basic procedures and
software solution, 1st ed., SSOAR, Klagenfurth, Austria, 2014. URL: https://www.ssoar.
info/ssoar/handle/document/39517.
[26] J. Saldaña, The coding manual for qualitative researchers, 2nd ed., SAGE, Los Angeles,
2013.
[27] M. Grootendorst, BERTopic: Neural topic modeling with a class-based TF-IDF procedure,
arXiv Working Paper 2203.05794, 2022. doi:10.48550/arXiv.2203.05794.
[28] C. Ullstein, M. Hohendanner, J. Grossklags, What people think about genAI and FPT, and
what policymakers want to know laypeople’s opinion on: A reality check, Working Paper,
Technical University of Munich, 2024.
[29] M. Hohendanner, C. Ullstein, G. Socher, J. Grossklags, “Good and scary at the same
time”—Exploring citizens’ perceptions of a prospective metaverse, IEEE Pervasive
Computing 23 (2024) 27–36. doi:10.1109/MPRV.2024.3366112.
[30] M. Hohendanner, C. Ullstein, D. Miyamoto, E. F. Hufman, G. Socher, J. Grossklags,
H. Osawa, Metaverse perspectives from Japan: A participatory speculative design case
study, Proceedings of the ACM on Human-Computer Interaction 8 (2024). doi:https:
//doi.org/10.1145/3686939.
[31] M. Hohendanner, C. Ullstein, Y. Buchmeier, J. Grossklags, Exploring the reflective space of
AI narratives through speculative design in Japan and Germany, in: Proceedings of the
2023 ACM Conference on Information Technology for Social Good (GoodIT), ACM, 2023,
pp. 351–362. doi:10.1145/3582515.3609554.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <given-names>P.</given-names>
            <surname>Lorenz</surname>
          </string-name>
          ,
          <string-name>
            <given-names>K.</given-names>
            <surname>Perset</surname>
          </string-name>
          ,
          <string-name>
            <given-names>J.</given-names>
            <surname>Berryhill</surname>
          </string-name>
          ,
          <article-title>Initial policy considerations for generative artificial intelligence (</article-title>
          <year>2023</year>
          ). URL: https://www.oecd-ilibrary.org/content/paper/fae2d1e6-en. doi:
          <volume>10</volume>
          . 1787/fae2d1e6-en.
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <given-names>Reclaim</given-names>
            <surname>Your Face</surname>
          </string-name>
          ,
          <year>2024</year>
          . URL: https://reclaimyourface.eu/de/.
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <given-names>Ban</given-names>
            <surname>Facial Recognition</surname>
          </string-name>
          ,
          <year>2024</year>
          . URL: https://www.banfacialrecognition.com/.
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <given-names>South</given-names>
            <surname>Wales</surname>
          </string-name>
          <string-name>
            <surname>Police</surname>
          </string-name>
          ,
          <article-title>Deployments for live facial recognition</article-title>
          ,
          <year>2023</year>
          . URL: https://www.south
          <article-title>-wales.police.uk/police-forces/south-wales-police/areas/about-us/ about-us/facial-recognition-technology/deployments-for-live-facial-recognition/.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          <article-title>[5] Future of Life Institute, Pause giant AI experiments: An open letter</article-title>
          ,
          <year>2023</year>
          . URL: https: //futureoflife.org/open-letter/
          <article-title>pause-giant-ai-experiments/.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <given-names>European</given-names>
            <surname>Commission</surname>
          </string-name>
          ,
          <article-title>Hiroshima process international guiding principles for advanced AI system</article-title>
          ,
          <year>2023</year>
          . URL: https://digital-strategy.ec.europa.eu/en/library/ hiroshima
          <article-title>-process-international-guiding-principles-advanced-ai-system.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <given-names>European</given-names>
            <surname>Parliament</surname>
          </string-name>
          ,
          <source>Artificial Intelligence Act: Deal on comprehensive rules for trustworthy AI</source>
          ,
          <year>2023</year>
          . URL: https:// www.europarl.europa.eu/news/en/press-room/20231206IPR15699/ artificial
          <article-title>-intelligence-act-deal-on-comprehensive-rules-for-trustworthy-ai.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <given-names>European</given-names>
            <surname>Commission</surname>
          </string-name>
          ,
          <source>AI Act enters into force</source>
          ,
          <year>2024</year>
          . URL: https://commission.europa.eu/ news/ai
          <article-title>-act-enters-</article-title>
          <string-name>
            <surname>force-</surname>
          </string-name>
          2024-08-01_
          <fpage>en</fpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <given-names>European</given-names>
            <surname>Commission</surname>
          </string-name>
          ,
          <source>AI Act</source>
          ,
          <year>2024</year>
          . URL: https://digital-strategy.ec.europa.eu/en/policies/ regulatory-framework-ai.
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <surname>G. Volpicelli,</surname>
          </string-name>
          <article-title>EU set to allow draconian use of facial recognition tech, say lawmakers</article-title>
          ,
          <source>Politico</source>
          (
          <year>2024</year>
          ). URL: https://www.politico.eu/article/ eu-ai
          <article-title>-facial-recognition-tech-act-late-tweaks-attack-civil-rights-key-lawmaker-hahn-warns/.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          [11]
          <string-name>
            <given-names>S.</given-names>
            <surname>Wachter</surname>
          </string-name>
          ,
          <article-title>Limitations and loopholes in the EU AI Act and AI Liability Directives: What this means for the European Union, the United States, and beyond</article-title>
          ,
          <source>Yale Journal of Law and Technology</source>
          <volume>26</volume>
          (
          <year>2024</year>
          )
          <fpage>671</fpage>
          -
          <lpage>718</lpage>
          . URL: https://law.yale.edu/sites/default/files/area/center/ isp/documents/wachter_26yalejltech671.pdf.
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          [12]
          <string-name>
            <given-names>M. T.</given-names>
            <surname>Baldassarre</surname>
          </string-name>
          ,
          <string-name>
            <given-names>D.</given-names>
            <surname>Caivano</surname>
          </string-name>
          ,
          <string-name>
            <given-names>B. Fernandez</given-names>
            <surname>Nieto</surname>
          </string-name>
          ,
          <string-name>
            <given-names>D.</given-names>
            <surname>Gigante</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Ragone</surname>
          </string-name>
          ,
          <article-title>The social impact of generative AI: An analysis on ChatGPT</article-title>
          ,
          <source>in: Proceedings of the 2023 ACM Conference on Information Technology for Social Good (GoodIT)</source>
          , ACM,
          <year>2023</year>
          , pp.
          <fpage>363</fpage>
          -
          <lpage>373</lpage>
          . doi:
          <volume>10</volume>
          .1145/3582515.3609555.
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>