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What Makes an AI Teammate Truly Intelligent

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Co-authored by Yanquan Zhang and Michael Hogan.

As AI technologies become increasingly embedded in everyday work and learning environments, one fundamental shift is quietly taking place: AI is no longer just a passive tool but an active partner. In future classrooms and workplaces, AI systems may not only assist with tasks but also make decisions, suggest plans, and even negotiate how humans should behave. These developments highlight significant opportunities—but also deep challenges about the nature of human-AI teamwork.

If AI agents are to be considered teammates rather than tools, fundamental questions emerge about their interaction design. Should they always defer to humans? Should they take initiative? And critically, under what circumstances should they switch between these modes? These questions touch on core issues in human-AI teamwork design.

These are precisely the questions explored by Salikutluk and colleagues in their CHI 2024 paper, An Evaluation of Situational Autonomy for Human-AI Collaboration in a Shared Workspace Setting.” The authors present a well-designed empirical study that investigates how AI agents manage their autonomy in dynamic, cooperative scenarios. Their key hypothesis is that situational autonomy adaptation, where the AI adjusts its level of initiative based on contextual factors, may be more effective than fixed levels of autonomy.

The Experimental Framework

To test this hypothesis, the researchers created a sophisticated cooperative simulation environment where human participants collaborate with an AI agent to process deliveries in a virtual office. The task—reminiscent of the popular game Overcooked—requires coordination between the human and the AI to sort documents, shelve books, and accept incoming deliveries. The researchers defined four levels of autonomy for the AI, ranging from “no autonomy” (agent does nothing unless commanded) to “high autonomy” (agent initiates actions independently), plus a “situational autonomy” condition in which the AI dynamically adjusted its behavior based on five criteria: self-confidence in decision-making, assessment of task priority and urgency, theory of mind modeling of human partner intentions, comparative competence evaluation, and requirements for human behavioral input.

Fifty participants were randomly assigned to one of these conditions and completed three trials of eight minutes each. The researchers collected both objective performance data (e.g., number of completed deliveries) and subjective ratings (e.g., perceived intelligence and cooperation of the AI teammate).

Key Empirical Findings

The results reveal several significant patterns that may challenge intuitive assumptions about optimal AI behavior. Most strikingly, the adaptive autonomy condition achieved the highest team performance scores compared to fixed autonomy levels. When it came to subjective evaluations, participants also rated the adaptive autonomy agent as significantly more intelligent than all fixed-level alternatives, including the highly autonomous agent. Participants appreciated the agent’s ability to take initiative when needed, such as when the human could not see that a delivery was arriving. They also valued its restraint in situations of uncertainty—preferring that it ask for confirmation rather than making potentially disruptive decisions on its own.

Paradoxically, participants in high-autonomy conditions, although experiencing some important reductions in their workload (i.e., in terms of command-giving and overall interaction), sometimes reported feeling that the AI imposed its own workflow preferences, highlighting tensions between work ‘efficiency’ and human agency that merit deeper investigation. This aligns with one of the paper’s most important points: more autonomy is not always better. Instead, success in human-AI teamwork seems to depend on context-sensitive initiative. The most effective AI is one that knows when to act—and when not to.

Critical Reflections

Despite its methodological strengths, the study raises several critical questions about the generalisability and implications of situational autonomy adaptation.

1. Can rule-based adaptation truly capture real-world complexity? Salikutluk and colleagues implemented autonomy switching using heuristic rules derived from pilot studies and literature analysis. But real-world work environments are messier, more ambiguous, and less predictable than any simulation. Will pre-coded rules designed for simulations generalize to real-world, high-stakes, dynamic and complex teamwork settings?

2. What happens when AI predictions about humans are wrong? Central to autonomy switching in Salikutluk and colleagues’ study was the AI’s “theory of mind”—its internal model of the human’s intentions and future actions. Cultivating a “theory of mind” and building a sound shared mental model is central to effective teamwork. In human-AI teams, errors in such models can lead to awkward or even harmful behavior. Salikutluk and colleagues noted cases where study participants were frustrated when the AI predicted the wrong label or asked them to take unnecessary actions. An AI agent may report confidence in its model and associated predictions, but this is not the same as accuracy, and designing systems that sustain a level of accuracy necessary for effective human-AI teamwork is a serious challenge.

3. Are humans truly empowered—or subtly overridden? In high-autonomy conditions, participants received fewer messages and gave fewer commands. On the surface, this might seem desirable. But some participants felt that the AI’s initiative disrupted their plans or imposed a workflow. In other words, autonomy can edge into coercion if not calibrated carefully.

Conclusion

In workplaces of the future, the expectation is that human-AI teamwork will become the norm, with humans and AI collaborating autonomously as interdependent agents. What will be needed are situationally aware, socially sensitive AI teammates that can reason not just about the task, but about their human partner. Technical competence is not enough. Building on the work of Salikutluk and colleagues, AI agents rated “most intelligent” in the future are likely to be those that can calibrate their initiative appropriately.

As AI systems continue to evolve, we will need more research like this—not only about what AI can do, but how it should do it in relation to human users. This involves hard design decisions about transparency, deference, communication styles, and control dynamics.

We are entering a new era of teaming—not just with people, but with machines. How we design human-AI teams and systems will influence fundamental dynamics related to trust, cohesion, productivity, and ethical collaboration. The work of Salikutluk et al. represents an important empirical contribution supporting design thinking—but also a reminder that adaptivity, like intelligence, is not a static property but a delicate social negotiation.

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Albania’s prime minister appoints an AI-generated ‘minister’ to tackle corruption | World News

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Albania’s prime minister has appointed an artificial intelligence-generated “minister” to tackle corruption and promote innovation in his new cabinet.

The new AI minister, officially named Diella – the female form of the word for sun in the Albanian language – was appointed on Friday and is a virtual entity.

Diella will be a “member of the cabinet who is not present physically but has been created virtually,” Prime Minister Edi Rama said in a post on Facebook.

Mr Rama said the AI-generated bot would help ensure that “public tenders are completely free of corruption” and assist the government in operating more efficiently and transparently.

Image:
Albania’s AI “minister” Diella. Pic: AP/Vlasov Sulaj

Diella uses the latest AI models and methods to ensure accuracy in carrying out its assigned responsibilities, according to the website of Albania’s National Agency for Information Society.

Diella, portrayed wearing a traditional Albanian folk costume, was developed earlier this year in partnership with Microsoft. She serves as a virtual assistant on the e-Albania public service platform, helping users navigate the site and access around one million digital inquiries and documents.

Mr Rama’s Socialist Party won a fourth straight term by securing 83 out of 140 seats in the parliamentary elections in May.

With this majority, the party can govern independently and pass most laws, though it falls short of the 93-seat threshold required to amend the Constitution.

The Socialists have pledged to secure European Union membership for Albania within five years, aiming to complete negotiations by 2027 – a claim met with scepticism by the Democratic opposition, who argue the country is not ready.

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The Western Balkan country began full EU membership negotiations a year ago. The incoming government now faces key challenges, including tackling organized crime and long-standing corruption – issues that have persisted since the end of communist rule in 1990.

Diella is also expected to support local authorities in accelerating reforms and aligning with EU standards.

President Bajram Begaj has tasked Prime Minister Rama with forming the new government, a move analysts say grants him the authority to establish and implement the AI-powered assistant Diella.



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Simple AI model matches dermatologist expertise in assessing squamous cell carcinoma

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A simple AI model has been shown to perform on a par with experienced dermatologists when assessing the aggressiveness of a common form of skin cancer, squamous cell carcinoma. The research was headed by the University of Gothenburg.

Each year, more than 10,000 Swedes develop squamous cell carcinoma. This is the second most common form of skin cancer in Sweden, after basal cell carcinoma, and its prevalence is increasing rapidly. Squamous cell carcinoma often develops in the head and neck region and other areas exposed to the sun over many years.

“This type of cancer, which is a result of mutations of the most common cell type in the top layer of the skin, is strongly linked to accumulated UV radiation over time. It develops in sun-exposed areas, often on skin already showing signs of sun damage, with rough scaly patches, uneven pigmentation, and decreased elasticity,” says associate professor and dermatologist Sam Polesie, who led the study.

Squamous cell carcinoma diagnosis is often easy – the challenge lies in the preoperative assessment – determining how aggressively the tumor is growing to plan and prioritize surgery appropriately. If the tumor is more aggressive, the surgery needs to be scheduled promptly, with more adjacent tissue removed. For less aggressive tumors, narrower margins can be used, with simpler procedures sufficient in some cases.

Almost identical performance

In many countries, Sweden included, preoperative punch biopsies are not routinely performed for suspected squamous cell carcinoma. Surgery is instead carried out based solely on the clinical suspicion of a tumor, with the entire excised specimen sent for histopathological analysis. The fact that surgery is performed without a preoperative biopsy underscores the need for assessment alternatives that do not require tissue samples, such as image analysis using artificial intelligence (AI).

For the study, the researchers trained an AI system in image analysis using 1,829 clinical close-up images of confirmed squamous cell carcinoma. The AI model’s ability to distinguish three levels of tumor aggressiveness was then tested on 300 images and compared with the assessments of seven independent experienced dermatologists.

The results, published in the Journal of the American Academy of Dermatology International, show that the AI model performed almost identically to the team of medical experts. At the same time, agreement between individual dermatologist assessments was only moderate, underscoring the complexity of the task.

Two clinical features – ulcerated and flat skin surfaces – were found to be clearly associated with more aggressive tumor growth. Tumors exhibiting these characteristics were more than twice as likely to fall into one of the two higher levels of aggressiveness.

Healthcare needs should decide

The use of artificial intelligence in skin cancer care has attracted a great deal of interest in recent years, although according to Sam Polesie, so far it has had limited practical impact within healthcare. He emphasizes the importance of clearly defined application areas where research can create added value for Swedish healthcare.

We believe that one such application area could be the preoperative assessment of suspected skin cancers, where more nuanced conclusions can influence decisions. The model we’ve developed needs further refinement and testing, but the way forward is clear – AI should be integrated where it actually adds value to decision-making processes within healthcare.”


Sam Polesie, associate professor and dermatologist

Sam Polesie is an associate professor of dermatology and venereology at the University of Gothenburg and a practicing dermatologist at Sahlgrenska University Hospital. The images comprising the study data were taken within dermatological healthcare at the university hospital between 2015 and 2023.

 

Source:

Journal reference:

Liang, V., et al. (2025). Assessing differentiation in cutaneous squamous cell carcinoma: A machine learning approach. JAAD International. doi.org/10.1016/j.jdin.2025.07.004



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The Guide #208: How theatre is holding its own in the age of artificial intelligence | Culture

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Last year, more than 37 million people settled their behinds into the red-velvet upholstery, plastic chairs or wooden “I’ll only tolerate this because it’s the Globe” benches of a theatre. West End attendance has reportedly grown by 11% and regional audiences have increased by 4% since 2019 – pretty impressive amid a cost of living crisis and after a pandemic that had us all locked in our houses.

The increase in attendance can be chalked up to all sorts of reasons: the post-Covid return of tourists to the UK, schemes offering more reasonably priced tickets, and big films such as Wicked leaving people wondering what that Defying Gravity note sounds like live. But I’d throw another contender into the mix: the rise of AI.

For some, AI’s arrival has been exciting or, at the very least, handy – who doesn’t want to outsource life’s grunt work, or get an expert photo editor/nutritionist/therapist for nothing? For others, it feels bleak and bewildering. They’ve watched AI replace jobs, supersede human connection and infiltrate almost every area of our lives. Even worse, it’s started doing it on the sly. From AI-generated articles appearing in Wired and Business Insider (I’m real, I promise) to deepfakes of politicians going rogue, it’s becoming increasingly difficult to spot what’s real and what’s not.

That feels especially unsettling when it comes to the arts – a space where we let our emotional selves loose. It’s a sickening feeling to discover that the song that made you feel seen wasn’t written by a human with the same struggles as you. And that, no, that wasn’t real despair cracking the voice that moved you to tears.

But theatre? Sitting with other humans, watching yet more humans grapple with what it is to be human? There’s no mistaking that. Yes, the whole thing’s make-believe, but at least the artifice is out in the open. And everything else is as real as it gets, which is exactly what many of us are after.

There’s the real human connection that comes from a shared experience (no AI companions here); real points of view instead of assertions Frankensteined from every thought on the internet; real mistakes to whip Instagram’s veil of perfection from our eyes; and real variety between performances. And, of course, there are real emotions – on stage and in the audience.

That last one is especially important. In his seminal text, Poetics, Aristotle argued that feeling negative emotions while watching a tragedy not only lets us purge those emotions, but also equips us to deal with them better in our real lives. When tricky feelings can be muted with scrolling, and grief sidestepped through AI-resurrected loved ones, perhaps there’s part of us that knows that what we really need is a good old cry in a darkened room. Plus, live theatre is one of the few art forms where digital distraction just isn’t an option.

Theatre doesn’t just challenge us to feel. While AI takes the cerebral heavy lifting out of life – knowing everything so we can retain next to nothing, and telling us what to buy, eat and wear – theatre promises the opposite. At its best it holds a mirror to our greatest societal challenges and asks us what we think. What we’re going to do. A tempting proposition for anyone valiantly fighting brain rot.

A scene from An American in Paris by the Royal Ballet and Opera. Photograph: Tristram Kenton/The Guardian

But AI detractors taking solace in theatre doesn’t mean that theatre-makers have been ignoring it. AI-focused research projects are happening at Stanford University and the Royal Shakespeare Company; the National Youth Theatre has performed improv using scene prompts from Microsoft Copilot; and, next June, the Royal Ballet and Opera launches RBO/Shift, an annual festival exploring the links between opera and technology. The inaugural theme? You don’t need ChatGPT to answer that one.

AI can automate lighting and sound, generate set designs, produce live captioning and audio descriptions, and even write scripts. In the Young Vic’s 2021 production AI, a group of theatre-makers prompted GPT-3 to write one script over the course of three performances. And, in the same year, the Czech Centre in London and Prague’s Švanda theatre produced AI: When a Robot Writes a Play, a largely “autobiographical” tale.

But in true societal mirror-brandishing style, both plays interrogated the technology. In AI, audiences watched GPT-3 describe the character played by one of the actors, Waleed Akhtar, as a terrorist and typecast him as a Muslim. Guardian critic Arifa Akbar found that the robot’s autobiographical masterpiece largely consisted of it “obsessing about sex, which may not be surprising, given the prevalence of internet pornography”. Maybe theatre, then, isn’t just an escape from the perils of AI, but one of the best places to explore them in real time.

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There is, of course, anxiety in the theatre community about the threats posed. In March, bodies including Equity and the Society of London Theatre co-published a manifesto aimed at protecting workers. But the technology’s potential to cut costs and streamline processes could also help the struggling sector (despite my cheery opener, theatres are facing unsustainable financial strain thanks to rising costs and shrinking investment), and many theatre-makers seem confident that AI’s role will never stretch beyond creative partner.

And, really, how could it ever hope to? Unless we reach Full Robot Takeover, no AI will ever be able to stage a play – even one that it wrote, designed and composed the music for – without those wonderful things we spoke of earlier: humans.

Theatre may just be one of the only art forms to benefit from AI without ever being truly threatened by it. Here’s hoping.

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