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Commentary: Should we use artificial intelligence to recreate our deceased loved ones?

Why would it be right or wrong, ethically desirable or reprehensible, to develop a conversational robot that can mimic a deceased loved one's identity? This researcher takes a closer look at controversial questions surrounding deadbots.

Commentary: Should we use artificial intelligence to recreate our deceased loved ones?

A robot modelled on mankind's oldest social interface: Humans.

BARCELONA, Spain: Machine learning systems are increasingly worming their way into our everyday lives, challenging our moral and social values, and the rules that govern them. 

These days, virtual assistants threaten the privacy of our homes, news recommenders shape the way we understand the world, risk prediction systems tip social workers on which children to protect from abuse, and data-driven hiring tools also rank your chances of landing a job.

However, the ethics of machine learning remains blurry for many. I was particularly struck by the case of Joshua Barbeau, a 33-year-old man who used a website called Project December to create a conversational robot a chatbot that would simulate conversation with his deceased fiancee, Jessica.


Known as a deadbot, this type of chatbot allowed Barbeau to exchange text messages with an artificial “Jessica”. Despite the ethically controversial nature of the case, I rarely found materials that went beyond the mere factual aspect and analysed the case through an explicitly normative lens: Why would it be right or wrong, ethically desirable or reprehensible, to develop a deadbot?

Before we grapple with these questions, let’s put things into context: Project December was created by games developer Jason Rohrer to enable people to customise chatbots with the personality they wanted to interact with, provided that they paid for it.

A person conversing with a chatbot. (Photo: iStock/Blue Planet Studio)

The project was built drawing on an API of GPT-3, a text-generating language model by the artificial intelligence research company OpenAI. Barbeau’s case opened a rift between Rohrer and OpenAI because the company’s guidelines explicitly forbid GPT-3 to be used for sexual, amorous, self-harm or bullying purposes.

Calling OpenAI’s position hyper-moralistic and arguing that people like Barbeau were “consenting adults”, Rohrer shut down the GPT-3 version of Project December.

While we may all have intuitions about whether it is right or wrong to develop a machine-learning deadbot, spelling out its implications hardly makes for an easy task. This is why it is important to address the ethical questions raised by the case, step by step.


Since Jessica was a real (albeit dead) person, Barbeau consenting to the creation of a deadbot mimicking her seems insufficient. Even when they die, people are not mere things with which others can do as they please. 

This is why our societies consider it wrong to desecrate or be disrespectful to the memory of the dead. In other words, we have certain moral obligations towards the dead, insofar as death does not necessarily imply that people cease to exist in a morally relevant way.

Likewise, the debate is open as to whether we should protect the dead’s fundamental rights (for example, their privacy and personal data). Developing a deadbot replicating someone’s personality requires great amounts of personal information, such as social network data (see what Microsoft or Eternime proposes), which have proven to reveal highly sensitive traits.

If we agree that it is unethical to use people’s data without their consent while they are alive, why should it be ethical to do so after their death? In that sense, when developing a deadbot, it seems reasonable to request the consent of the one whose personality is mirrored in this case, Jessica.


Thus, the second question is: Would Jessica’s consent be enough to consider her deadbot’s creation ethical? What if it were degrading to her memory?

The limits of consent are, indeed, a controversial issue. Take as a paradigmatic example the “Rotenburg Cannibal”, who was sentenced to life imprisonment despite the fact that his victim had agreed to be eaten.

In this regard, it has been argued that it is unethical to consent to things that can be detrimental to ourselves, be it physically (such as selling one’s own vital organs) or abstractly (like alienating one’s own rights).

In what specific terms something might be detrimental to the dead is a particularly complex issue that I will not analyse in full. It is worth noting, however, that even if the dead cannot be harmed or offended in the same way as the living, this does not mean that they are invulnerable to bad actions, nor that these are ethical. 

The dead can suffer damages to their honour, reputation or dignity (for example, posthumous smear campaigns), and disrespect toward the dead also harms those close to them. Moreover, behaving badly toward the dead leads us to a society that is more unjust and less respectful of people’s dignity overall.

Finally, given the malleability and unpredictability of machine learning systems, there is a risk that the consent provided by the person mimicked (while alive) does not mean much more than a blank check on its potential paths.

Taking all of this into account, it seems reasonable to conclude if the deadbot’s development or use fails to correspond to what the imitated person has agreed to, their consent should be considered invalid. Moreover, if it clearly and intentionally harms their dignity, even their consent should not be enough to consider it ethical.

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A third issue is whether artificial intelligence systems should aspire to mimic any kind of human behaviour (irrespective here of whether this is possible).

This has been a long-standing concern in the field of AI and it is closely linked to the dispute between Rohrer and OpenAI. Should we develop artificial systems capable of, for example, caring for others or making political decisions? 

It seems that there is something in these skills that make humans different from other animals and from machines. Hence, it is important to note that instrumentalising AI toward techno-solutionist ends, such as replacing loved ones, may lead to a de-valuation of what characterises us as human beings.


The fourth ethical question is who bears responsibility for the outcomes of a deadbot especially in the case of harmful effects.

Imagine that Jessica’s deadbot autonomously learned to perform in a way that demeaned her memory or irreversibly damaged Barbeau’s mental health. Who would take responsibility? 

AI experts answer this slippery question through two main approaches: First, responsibility falls upon those involved in the design and development of the system, as long as they do so according to their particular interests and worldviews.

Second, machine learning systems are context-dependent, so the moral responsibilities of their outputs should be distributed among all the agents interacting with them.

I place myself closer to the first position. In this case, as there is an explicit co-creation of the deadbot that involves OpenAI, Jason Rohrer and Joshua Barbeau, I consider it logical to analyse the level of responsibility of each party.

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First, it would be hard to make OpenAI responsible after they explicitly forbade using their system for sexual, amorous, self-harm or bullying purposes.

It seems reasonable to attribute a significant level of moral responsibility to Rohrer because he explicitly designed the system that made it possible to create the deadbot, did it without anticipating measures to avoid potential adverse outcomes, was aware that it was failing to comply with OpenAI’s guidelines, and profited from it.

And because Barbeau customised the deadbot drawing on particular features of Jessica, it seems legitimate to hold him co-responsible in the event that it degraded her memory.


So, coming back to our first, general question of whether it is ethical to develop a machine-learning deadbot, we could give an affirmative answer, if these three conditions are fulfilled. First, both the person mimicked and the one customising and interacting with it have given their free consent to as detailed a description as possible of the design, development and uses of the system.

Second, developments and uses that do not stick to what the imitated person consented to or that go against their dignity are forbidden. 

Third, the people involved in its development and those who profit from it take responsibility for its potential negative outcomes. Both retroactively, to account for events that have happened, and prospectively, to actively prevent them to happen in the future.

This case exemplifies why the ethics of machine learning matters. It also illustrates why it is essential to open a public debate that can better inform citizens and help us develop policy measures to make AI systems more open, socially fair and compliant with fundamental rights.

Sara Suarez-Gonzalo is a Postdoctoral Researcher at the Universitat Oberta de Catalunya. This commentary first appeared in The Conversation.

Source: CNA/geh