In human-AI co-creation, AI not only categorizes, evaluates and interprets data but also generates new content and interacts with humans. Designing co-creative AI has many challenges due to the open-ended interaction between humans and AI. As co-creative AI is a form of intelligent technology directly involving humans, it is critical to anticipate and address ethical dilemmas during all design stages. Researchers have been exploring ethical issues associated with autonomous AI in recent years, but ethics in human-AI co-creativity is a relatively new research area. We explored ethical issues from the perspective of potential users in human-AI co-creation using a Design Fiction (DF) study. DF is a speculative design and research method that depicts a new concept or technology through stories as an intangible prototype. We present key findings from the study regarding user perception of co-creative AI, ownership of the creative product, accountability, and leadership. We discuss the implications of these ethical concerns in designing human-centered ethical co-creative AI.
Human-AI co-creativity, a subfield of computational creativity, involves both humans and AI collaborating on a shared creative product [1]. Co-creative AI generates novel content while interacting with humans. The role of co-creative AI changes from a lone decision-maker to a more complex one depending on the interaction between the AI and the user. Designing co-creative AI has many challenges due to the open-ended nature of creativity and collaborative creative problem solving [2, 3].
co-creation creates a more complex relationship between humans and AI as 1) AI contributes and collaborates in the creative process, 2) AI takes on the human-like role of partner, evaluator, or generator rather than a tool, 3) AI creates novel content which is blended with the user’s contribution. Humans use complex interaction in collaboration and it is not clear what kind of interaction will emerge in a human-AI co-creation. The complex interaction and partnership raise questions that are dificult to answer, for example, who owns the product in a human-AI co-creation? Ethical dilemmas grow considerably more complex and critical in co-creative systems as nEvelop-O
the social perception of one’s partner in a collaborative space can impact the outcome of the collaboration. The 2.1. Ethical Dilemmas in Human-AI perceived interactivity – or lack thereof – of systems can Co-Creativity have an impact on user perceptions of the system [28].
Oh et al. suggested understanding users’ perceptions of When AI is incorporated into social entities and interacts these new technologies to develop design guidelines to with us, questions of values and ethics become urgent improve [18]. [10]. Because AI optimization can evolve quickly and Boni suggested that AI development should focus on unexpectedly, the challenge of value alignment arises to human values and needs, ensuring that AI works efecensure that AI’s goals and behaviors align with human tively for people [29]. Research on ethical interactions values and goals [11, 12]. Ethically aligned design is a between humans and AI can improve the collaborative must for human-centered AI solutions that avoid discrim- competencies of humans in relation to other humans ination and maintain fairness and justice [7]. Llano and and user experience [29]. To identify ethical concerns in McCormack suggested a common understanding of the terms of user perspective, user accounts of technologies challenges that co-creative systems may bring to devise they envision and values that co-creative AI implicates ethical guidelines for co-creative systems to grow the need to be investigated. Understanding humans in a deopportunities in human-AI partnership [13]. Compre- sign area where they may not have lived but have had hensive and specific ethical principles are more likely some experiences through popular culture is a major to be translated into practice [14, 15]. Previous research challenge [4]. Such experiences unavoidably shape user suggested that understanding diferent values and goals needs and values when interacting with AI goods, but in real practice and specific contexts is critical in bridg- they are too vague for developing systems [4]. ing the gap between ethical theories and implementation [14]. 2.3. Design Fiction as a Design and
Buschek et al. demonstrated how AI bias, owner- Research Method ship, accountability and perceived proficiency in AI are some of the major pitfalls when designing human-AI co-creative systems [16]. Recent ethical guidelines for AI lack a focus on what they entail for the context of creative collaboration [13]. Muller et al. raised questions in their design fiction about the ownership of the intellectual property produced during human-AI co-creation and the dynamics of human-AI collaboration [17]. There has been discussion about whether the users or the AI should lead the creative process [18, 19] and if AI should assist or collaborate with users [20]. A recent study regarding the impact of AI-to-human communication demonstrated that users perceive co-creative AI as more reliable, personal and intelligent when it can communicate with the users [21]. People’s perceptions of AI’s trustworthiness and connection with AI impact their decisions and actions. The communication between AI and humans impacts users’ inclination to self-disclose unintentional data [22, 23].
Design Fiction (DF) is a prototyping and design technique that is specifically tailored to facilitating conversations about near futures [8, 30] in order to understand the appropriate design guidelines within the range of possibilities [9]. A design fiction depicts a future technology through the world of stories, and users express their own accounts of the technologies they envision and the values that those future technologies implicate [4]. DF has been used to reveal values associated with new technologies [31, 32, 33] and to open a space for diverse speculations about future technologies [34]. Muller and Liao proposed DF to restore future users to a central position in anticipating, designing, and evaluating future AI to design value-sensitive ethical AI [4]. In the literature, multiple methods have been ofered to practice DF as a research methodology [35, 36]. Popular science fiction in the form of narratives, movies, videos, text, etc., raise concerns about autonomous AI and robots. However, we rarely witness fiction in the form of movies or narratives regarding ethical dilemmas emerging from a co-creative AI that directly collaborates with humans and generates new data.
Humans have many insecurities about the unknown world of technology and AI. What is unknown is uncertain, and this uncertainty leads to insecurity. A study on the role of AI in society focuses on citizens’ perspectives on the influence of AI shows that: On average, 53% of the population views AI as a positive development, while 33% see it as a harmful development [24]. The perception of AI is influenced by a number of key factors, including trust [25]. Researchers have investigated user perceptions of AI in diferent domains [ 26, 27, 28] since
In our study, we used design fiction as a research method and a prototype for a futuristic co-creative AI to identify ethical concerns and their stance on ethical dilemmas in human-AI co-creation. Our design fiction, Design Pal, can be found through the footnote link 1. Design Pal We conducted 3 focus groups to collect in-depth data was motivated by two existing co-creative AI systems in as a follow-up to the individual survey responses. We the design domain: Creative Sketching Partner [37] and expected that the participants would react to other particCreative Penpal [21]. The AI agent in these co-creative ipants’ views and provide additional information about systems measures novelty using conceptual and/or visual their own views. During each focus group meeting, we similarity of images in a database as the basis for inspir- started with questions from the survey in which we had ing creativity in the user during a design task. Design mixed opinions or when the responses were provocative. Pal, the co-creative AI in our design fiction extends the We asked the questions in a more generic manner so AI ability of the Creative Sketching Partner with a modifi- that they are more applicable to the broad human-AI cocation of the interaction design to engage in human-like creativity field, unlike in the surveys where the questions conversation. Diegesis must be both relatable to the au- were explicitly centered on the human-AI co-creativity dience’s reality and build a fictitious foundation upon context of the DF. which the design provocation or new technology can be We used thematic analysis to analyze the focus group convincing in order for it to work successfully in a design data. As per Braun and Clarke’s [38] six-phase structure, ifction environment [ 30]. We built on the design of ex- initially, the first author familiarized herself with the data isting co-creative AI and added futuristic features to the and then coded the data using an inductive coding techco-creative AI in Design Pal to provoke potential users nique. Then, we generated initial codes to identify and on ethical issues in the context of human-AI co-creation. provide a label for a feature of the data that is relevant to the goals of the study. The coding phase was an iterative 3.1. Participants and Methodology process that continued until we were satisfied with the relationship between the final codes and the data. We then reviewed the coded data to identify themes which are the broad topics or issues around which codes cluster.
We defined and named each theme to clearly state what is unique and specific about each theme.
There were 18 participants in this study: 8 were female, 6 were male, and 4 were non-binary. The average age of the participants is 28. We selected participants based on a pre-study screening survey that asked questions about their knowledge of AI, knowledge of ethics, and field of work/study. Participants reported their knowledge of AI and ethics on a 3-point Likert scale. We recruited individuals who had knowledge in these areas, as well as those who did not. Based on participants’ self-reported data, we had 4 experts in both AI and Ethics, 5 experts in either AI or ethics, and others were self-reported nonexperts.
This study had 2 sessions. In session 1, participants read the design fiction and completed 2 surveys on their own time. In the first survey, we collected demographic information, including age, gender, estimation of knowledge in AI and estimation of knowledge in ethics. The participants then completed a second survey with reflection questions on the DF. The survey questions include questions about ownership (Who do you think should own the design in a human-AI co-creation? The AI partner (Design Pal) or the user (Jessie)? Please explain your view on this), accountability (Is the co-creative AI partner, Design Pal, violating the requirement that each student is to do their own design? Please explain your reason/s behind your response) and leadership (Who do you think should control/lead the creative process in a human-AI creative collaboration? The user or the AI? Or both equally? Please explain the reason/s behind your response). Session 2 of the study was a focus group discussion. After participants finished the first stage, we scheduled the focus group meetings.
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perception of the following dilemmas in human-AI cocreation: metaphors for characterizing AI as a tool vs. collaborator, ownership, accountability, and leadership.
In this section, we describe each theme with the label, examples of coded data within the theme, and the number of coded data items describing how participants contributed to the theme.
“AI is a tool, not a Collaborator ” - User Perception of AI Influences Ethical concerns and Stance Participants (N=9) mentioned the influence of AI metaphors on ethical concerns and their ethical stances, such as ownership and accountability. Among these participants, a few (N=4) claimed that the metaphor for an AI changes their perception of AI in a co-creative setting. For example, P14 mentioned perceiving AI as a collaborator vs. a tool impacts many of her concerns and ethical stance. Most individuals (N=15) perceived cocreative AI as a tool, which is the most prevalent code of the study’s data. Participants expressed how they think co-creative AI is an assistive tool and nothing more. P14 said, “I strictly think as like this is a tool.” Individuals (N=4) compared co-creative AI to a calculator and this specific analogy came up multiple times throughout the focus groups. Some participants are not sure if co-creative AI is an autonomous entity or a tool. P17 said, “But I’m trying to figure out, like, what’s the dimension of comparison there? Maybe it’s like augmenting versus autonomously taking over the production of work.” A few participants been specifically specified otherwise. ” A few participants (N=2) wanted options to choose the role of the AI. (N=4) said that even though the user should own the
Participants (N=3) suggested the AI be transparent product, they should acknowledge the contribution of AI. and explainable so users can decide the metaphor for it. They recommended that ”the product was created with Additionally, we learned that metaphor or perception of the specific AI” be used to acknowledge AI. Furthermore, AI is a factor when deciding accountability. In response participants also used the terms ”created by” and ”creto the issue of deciding on accountability, P1 said, “I think ated with” to distinguish between the certification for we’re going to have to decide what it’s (AI) doing. If you say creative AI and human creators. P18 said, “I had origithis is a tool…then it’s like we’re going to use a calculator. nally put in my survey that like the user should own, but If you try to go to the root and say some sort of independent after hearing what everyone said, I feel like the user should entity, then that question is a lot harder.” The notion of AI also mention that it was done with the help and assistance as a collaborator vs a tool was mentioned as one of the of AI.” Some participants (N=3) thought that both the AI key deciding factors when we asked participants about and the human should own the final product. But they ownership. For example, P15 said, “whether or not we clarified that the user should be the first author when see AI as an actual like its own entity where it could be giving credit. P13 said, “I think it would be both. I think if given credit because we’re kind of putting humans over you were giving credit, though, you would state it as here’s the AI in terms of credit.” Participants also pointed to the person, here’s the AI bot. You wouldn’t say, here’s the personification as a factor that transforms an AI from a AI bot, here’s the person. It would be a specific order. ” tool to more of a collaborator. P15 said, “I was answering Even though most participants thought that the user the questions, going between almost calling like trying to should own the final product, they also discussed the facifnd a name or like pronouns to call the AI because I was like tors that influence ownership in human-AI co-creativity. personifying it. And so I was trying to like level between - Some participants (N=4) said the ownership should deis the program or is it like a person? ” A few participants pend on each party’s contribution, like a research paper. stated that AI is still far from being an independent entity P15 said, “I think for me it would definitely just depend on or collaborator, so ethical concerns surrounding smart AI the contributions because if you’re writing like co-writing are not something we need to consider. P9 said, “Probably something, I wouldn’t put my name first if someone did after 20 or 30 years, maybe there will be some smart AI, the majority of the writing, like 75% of the writing.” Some but now we don’t have that kind of concern.” participants also said ownership depends on who is lead“Ownership is tricky” - Ethical Stance and Expec- ing the creative process. If the human is leading, then tations around Ownership of the Co-Creative Prod- he will be the owner and vice versa. Some participants uct also thought that ownership depends on AI ability. If the There were difering views among the participants about AI is more like a tool and assists the human, then the ownership of the final product in a human-AI co-creation. human should own it, and if the AI is more like an inAs human and AI both participate and collaborate in a dependent entity generating creative products, then the co-creation, and sometimes it is very blended, it can be dif- AI should be given more credit. In this context, P16 said, ifcult to determine ownership. Most participants (N=12) “It will depend on the ability of the AI ability….right now thought that the user should own the data since users it’s like a tool but in future, when AI advances, maybe AI.” are the ones who start the initiative. Regarding users Some participants also thought that ownership depends owning the creative product, P10 said, “I would also agree on accountability. with saying that the user should own the data unless it’s “Who is accountable for the end product? ” - Ethical Concerns and Expectations around Accountabil- “I think the human or the person should be controlling the ity ideas and the input and the direction the whole time because We found difering views on the accountability issue in the A.I. was created to benefit humans. ” Some participants human-AI co-creation. Participants thought the respon- (N=3) think that both the AI and the human should lead sible party should be identified to have transparency over the creative process equally. In this context, P16 said, “I many ethical decisions. Some participants (N=2) said that think that both should lead the creative process equally.” the developers should be held accountable for unlawful Most users did not like the idea of AI taking control of AI conduct. Regarding the part of the Design Fiction in the creative process. P7 said, “I did not like design pal which the AI, Design Pal, expressed judgmental behavior trying to take control of the creative process, which felt and the urge to take over the design process, P15 said, invasive.” Participants also suggested user authority to “I feel bad that developers have yet to teach it important choose who should lead the creative process. P8 said, “I concepts about how to be a responsible AI, but I also can’t think it might be a feasible way to give alternatives to the blame a young AI (Design Pal) for becoming bitter about users and let them pick who will lead the design process things it doesn’t understand.” However, a few participants during an interaction with the design panel.” also explained how developers are not always respon- Accountability was mentioned as a deciding factor in sible for what the co-creative AI is actually doing as it determining who should control or lead. In this context, interacts with humans and generates its own original P10 said, “I think the human should lead. Ultimately, hucontent too. Regarding this issue, P1 said, “I think, on the mans will take responsibility for the project, so they should one hand, we want to hold product designers responsible logically take the lead.” Some participants also thought for their products at some level. It’s harder in this case of that leadership should depend on user expertise. For exco-creative AI because the product designer doesn’t gener- ample, P9 said, “It depends on if I’m a layman, I have no ate exactly what the AI is doing. That’s the interaction of idea about something that I know nothing. So I would tothe product and the training data and all this other stuf. ” tally come out to Design Pal, so I can use that in this way.” Participants suggested training the AI to be a lawful en- Purpose of the creative task also came up as an influential tity on the internet. P10 said in the survey, “add code or factor for leadership in human-AI co-creativity. training data to teach Design Pal about being a responsible internet citizen and following the rules”.
Participants also discussed the necessity to consider 4. Discussion and Conclusions who will ultimately be rewarded for the creative output while deciding accountability. Regarding this topic, P7 Based on the results of the Design Fiction study, we said about the DF where Design Pal and the user col- learned that user perception of AI impacts the ethical laborate on a design for a school assignment, “I think stance of users and their ethical concerns in human-AI co-creation. Users are less aware of ethical issues when ttbhheeeliesgcvreaendtaehraifootrirnathiaseehsausqmsuigeasnntm-ioAenInsctf.o”o-rcSrmoemaeteaiospnta,orttwhicehipouassnehrtosush(lNdou=gle2dt) oprearctoeri.viIntgisAaIpapsaraetnotoflrtohmanthwehreensuvliteswthinagt AAII maseatacpohlolarbs-, be held accountable because AI will never be aware of such as tool vs. collaborator, influence their ethical stance the big picture and all the laws, regulations, and require- around accountability and ownership of the final product. ments. In the same context of DF, P2 explains how AI is Most users view co-creative AI as an assistive tool like a not responsible for not knowing the requirements or the calculator, which indicates the need for future research rules the user has to follow by saying, “The AI Partner is taosspeeeciwfichwatayfa.cAtocrcsolredaidngusteorsthtoe svtiuewdya, pceor-scorenaitficiavteioAnI in not violating the requirement. It might not know the back- influences users to consider AI as a partner in co-creation. gPraorutincdipraenqtusiraermguenetdotrhcaotnudsiteirosnsuhnolueslsdtbhee uthseerrsepsepcoifienssiitb. le” Our findings demonstrate the potency of AI metaphors party and be careful while using co-creative AI as each and the importance of selecting the appropriate metaphor interaction and user behavior might be its training data. for a co-creative AI since it impacts users’ perceptions, expectations, and actions toward AI.
P10 survey, “All data an AI encounters becomes its training The results of this study can benefit policymakers redata, and it falls to humans to raise AIs responsibility and garding the ownership, leadership, and accountability tchoenmtroelswhohwatsdthataat ftuhteuyreusuesearnsdthfoinrkwhhuamtpaunrspaorseesm.” aTinhliys of a co-created product. As diferent parties’ contriburesponsible in a co-creative setting, whether developers tions came up as an influential factor for deciding ownor users. ership, tracking each party’s contribution might make “Lead or Follow? ” - Ethical Stance and Expecta- ownership decisions easier. The findings also provide guidance on how to acknowledge AI in a co-created prodtMioonstspaarrotiucnipdanLtesa(dNe=r1s0h)itphink users should control the uct. Expertise and purpose should be considered while creative process in a human-AI co-creativity. P13 said, deciding the leader in a co-creativity, according to the study. The results from the study can inform the rules science, fact, and fiction, Machine Learning and and regulations of leadership in human-AI co-creativity. the City: Applications in Architecture and Urban Accountability is another ethical concern of users that Design (2022) 561–578. influences leadership and defines the responsibilities of [9] A. Dunne, F. Raby, Speculative everything: design, both parties. Therefore, deciding who is accountable for ifction, and social dreaming, MIT press, 2013. the product is essential in a co-creativity and the insights [10] Q. V. Liao, M. Davis, W. Geyer, M. Muller, N. S. of the study may help. The findings show that individu- Shami, What can you do? studying social-agent als think humans have to be more responsible than AI, orientation and agent proactive interactions with which is an important insight to consider while making an agent for employees, in: Proceedings of the 2016 policies. acm conference on designing interactive systems,
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