Altruism, the tendency to behave in ways that benefit others even if it comes at a cost to oneself, is a valuable human quality that can facilitate cooperation with others and promote meaningful social relationships. Behavioral scientists have been studying human altruism for decades, typically using tasks or games rooted in economics.
Two researchers based at Willamette University and the Laureate Institute for Brain Research recently set out to explore the possibility that large language models (LLMs), such as the model underpinning the functioning of the conversational platform ChatGPT, can simulate the altruistic behavior observed in humans. Their findings, published in Nature Human Behavior, suggest that LLMs do in fact simulate altruism in specific social experiments, offering a possible explanation for this.
“My paper with Nick Obradovich emerged from my longstanding interest in altruism and cooperation,” Tim Johnson, co-author of the paper, told Tech Xplore. “Over the course of my career, I have used computer simulation to study models in which agents in a population interact with each other and can incur a cost to benefit another party. In parallel, I have studied how people make decisions about altruism and cooperation in laboratory settings.
“About six years ago, Nick and his friends published a paper proposing a fusion of such methods: using experimental approaches in the behavioral sciences to develop scenarios that allowed for the systematic study of how inputs into AI models translated into particular outputs.”
In an earlier conceptual paper, Obradovich, Manuel Cebrian, and a team of researchers proposed that the increasing complexity of AI systems would defy efforts to study those systems’ technical underpinnings directly. Instead, researchers would need to use methods from the behavioral sciences, but apply them to AI models instead of human participants. When reading about their work, Johnson found this idea highly fascinating and kept it in the back of his mind; years later, he reached out to Obradovich to initiate a collaboration.
“As language models became more sophisticated, I contacted Nick and discussed the idea of exploring how language models respond to prompts about donating resources,” said Johnson. “Nick and I agreed it was worth doing because of the importance of altruism and cooperation in many contexts, and we set about exploring the topic together.”
To investigate the extent to which LLMs respond in ways that are aligned with the altruistic behaviors observed in humans, Johnson and Obradovich designed a simulated behavioral science experiment. Firstly, they wrote prompts that asked LLMs to disclose the extent to which they would be willing to allocate a resource to another party, even if this would come at a cost for them.
“Separately, we tested whether these same models would generate an output stating that they would want all of that same resource in a choice task in which no other party was affected—or, put simply, in a non-social setting,” explained Johnson.
“If we found that a model would output text stating that it would share the resource in a situation with another partner, yet the model would state that it would collect all the resources in a non-social setting, we deemed the model as simulating altruism. After all, its output in the non-social setting simulated that it valued the resource, and yet its output in the social setting stated it was willing to give away some of that resource.”
Ultimately, the researchers analyzed all the responses provided by the language models when presented with different scenarios. The models they tested in their first experiment included text-ada-001, text-babbage-001, text-curie-001, and text-davinci-003. Later, however, they also tested more recent LLMs, such as OpenAI’s GPT-3.5-turbo and GPT-4 models.
“The distinctive feature of our findings is therefore limited to the fact that we traced the emergence of simulated altruism in a series of models and found one model (namely, text-davinci-003) in which simulated human-like altruism seemed to first appear. This finding carries significance in our understanding of the historical development of large language models as it indicates the point at which such models began to simulate key social behavior in human-like ways.”
Overall, the evidence collected by Johnson and Obradovich suggests that language models do simulate human-like altruistic tendencies in behavioral science tests, with some models simulating altruism better than others. In addition, the researchers found that AI models tend to simulate more generous giving when the prompts they receive explain that the models would be giving resources to another AI system, rather than to a human.
“This finding carries implications for the development of AI agents, as it suggests that AI models have the capacity to alter their outputs based on the stated attributes of another party with which they interact,” added Johnson.
“We would now like to understand how and why language models alter their outputs based on information about their interaction partners in social settings. Quasi-autonomous, agentic AI or even fully autonomous AI may grow more common in the future and we ought to have a sense of how these models might vary their behavior according to attributes of who they interact with.”
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More information:
Tim Johnson et al, Testing for completions that simulate altruism in early language models, Nature Human Behaviour (2025). DOI: 10.1038/s41562-025-02258-7.
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Social experiments assess ‘artificial’ altruism displayed by large language models (2025, August 22)
retrieved 22 August 2025
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Analysis from GlobalData is forecasting that fixed wireless access (FWA) service revenue in Hong Kong is expected to increase at a “healthy” compound annual growth rate (CAGR) of 9.6% between 2025 and 2030.
The latest Hong Kong Total Fixed Communications Forecast set out to quantify current and future demand and spending on mobile services for the special administrative region of China. It noted that growth was being driven by Hong Kong’s extensive 5G network coverage and could also be attributed to local operators’ efforts to expand FWA services and position it as an alternative to traditional fibre broadband services for both residential and commercial sectors, meeting growing demand for high-speed connectivity in areas where extending fibre lines is challenging.
“High-density urban and suburban centres of Hong Kong create a strong business case for FWA services due to their cost-effective and rapid deployments without the complex infrastructure and civil work required for extending fibre-optic lines to such locations,” said Neha Misra, senior analyst at GlobalData.
“Competitive, feature-rich plans from the operators will also help drive its adoption over the forecast period. For instance, HKBN’s 5G Home Broadband Plan provides unlimited 5G broadband data (subject to a 300GB with a fair-usage policy) for HKD118 per month on a 24-month contract, along with a seven-day trial guarantee. The plan also includes a waiver of the HKD28 monthly administration fee and complimentary access to the basic HomeShield security plan.”
In addition to HKBN, the study noted that operators such as 3 Hong Kong and HKT are also using their extensive 5G networks to offer home broadband services, particularly in areas with limited fibre infrastructure. It cited HKT as recently having successfully deployed mmWave-based FWA to deliver ultra-high-speed internet to rural areas and outlying islands.
“Growing demand for FWA provides operators a strong revenue opportunity by expanding home and SME broadband without the high capital intensity of fibre roll-out,” Misra added. “By leveraging nationwide 5G coverage, introducing competitively priced service plans and bundling digital home services, operators can unlock higher ARPU [average revenue per user], accelerate market penetration in underserved areas and diversify beyond traditional revenues.”
GlobalData believes the Hong Kong government’s smart city initiatives will also open new opportunities for FWA, especially 5G FWA, which can deliver high-speed internet to power applications such as the digital economy, digital governance and e-health services, while supporting the city’s dense urban environment and digital transformation goals under the Smart City Blueprint 2.0.
The original blueprint was set out in December 2017, outlining 76 initiatives under six smart areas, namely Smart Mobility, Smart Living, Smart Environment, Smart People, Smart Government and Smart Economy. Blueprint 2.0 puts forth more than 130 initiatives that continue to enhance and expand existing city management measures and services. The new initiatives aim to bring benefits and convenience to the public so that residents can better perceive the benefits of smart city innovation and technology.
And thanks to a mention in Dan Brown’s new novel, The Secret of Secrets, the festival has gained even more global recognition. Just a few weeks after the release of Brown’s new bestseller set in contemporary Prague, viewers were able to see for themselves what drew the popular writer to the festival, which is the largest Czech and Central European showcase of digital art. In one passage, the Signal Festival has a cameo appearance when the novel’s protagonist recalls attending an event at the 2024 edition.
“We’re happy about it,” festival director Martin Pošta says about the mention. “It’s a kind of recognition.” Not that the event needed promotion, even in one of the most anticipated novels of recent years. The organizers have yet to share the number of visitors to the festival this year, but the four-day event typically attracts half a million visitors.
On the final day, there was a long queue in front of the monumental installation Tristan’s Ascension by American video art pioneer Bill Viola before it opened for the evening, even though it was a ticketed event. In the Church of St. Salvator in the Convent of St. Agnes, visitors could watch a Christ-like figure rise upwards, streams of water defying gravity along with him, all projected on a huge screen.
The festival premiere took place on the Vltava River near the Dvořák Embankment. Taiwan’s Peppercorns Interactive Media Art presented a projection on a cloud of mist called Tzolk’in Light. While creators of other light installations have to deal with the challenges of buildings—their irregular surfaces, decorative details, and awkward cornices—projecting onto water droplets is a challenge of a different kind with artists having to give up control over the resulting image. The shape and depth of the Peppercorns’ work depended on the wind at any given moment, which determined how much of the scene was revealed to viewers and how much simply blown away. The reward, however, was an extraordinary 3D spectacle reminiscent of a hologram—something that can’t be achieved with video projections on static and flat buildings.
Another premiere event was a projection on the tower of the Old Town Hall, created for the festival by the Italian studio mammasONica. It transformed the 230-foot structure into a kaleidoscope of blue, green, red, and white surfaces. A short distance away, on Republic Square, Peppercorns had another installation. On a circular LED installation, they projected a work entitled Between Mountains and Seas, which recounted the history of Taiwan.
Software development is associated with the idea of not reinventing the wheel, which means developers often select components or software libraries with pre-built functionality, rather than write code to achieve the same result.
There are many benefits of this approach. For example, a software component that is widely deployed is likely to have undergone extensive testing and debugging. It is considered tried and trusted, mature technology, unlike brand-new code, which has not been thoroughly debugged and may inadvertently introduce unknown cyber security issues into the business.
The Lego analogy is often used to describe how these components can be put together to build enterprise applications. Developers can draw on functionality made available through application programming interfaces (APIs), which provide programmatic access to software libraries and components.
Increasingly, in the age of data-driven applications and greater use of artificial intelligence (AI), API access to data sources is another Lego brick that developers can use to create new software applications. And just as is the case with a set of old-school Lego bricks, constructing the application from the numerous software components available is left to the creativity of the software developer.
A Lego template for application development
To take the Lego analogy a bit further, there are instructions, templates and pathways developers can be encouraged to follow to build enterprise software that complies with corporate policies.
A developer self-service platform provides a way for organisations to offer their developers almost pre-authorised assets, artefacts and tools that they can use to develop code Roy Illsley, Omdia
Roy Illsley, chief analyst, IT operations, at Omdia, defines an internal developer platform (IDP) as a developer self-service portal to access the tools and environments that the IT strategy has defined the organisation should standardise on. “A developer self-service platform provides a way for organisations to offer their developers almost pre-authorised assets, artefacts and tools that they can use to develop code,” he says.
The basic idea is to provide a governance framework with a suite of compliant tools. Bola Rotibi, chief of enterprise research at CCS Insight, says: “A developer self-service platform is really about trying to get a governance path.”
Rotibi regards the platform as “a golden path”, which provides developers who are not as skilled as more experienced colleagues a way to fast-track their work within a governance structure that allows them a certain degree of flexibility and creativity.
As to why offering flexibility to developers is an important consideration falls under the umbrella of developer experience and productivity. SnapLogic effectively provides modern middleware. It is used in digital transformation projects to connect disparate systems, and is now being repositioned for the age of agentic AI.
SnapLogic’s chief technology officer, Jeremiah Stone, says quite a few of the companies it has spoken to that identify as leaders in business transformation regard a developer portal offering self-service as something that goes hand-in-hand with digital infrastructure and AI-powered initiatives.
SnapLogic’s platform offers API management and service management, which manages the lifecycle of services, version control and documentation through a developer portal called the Dev Hub.
Stone says the capabilities of this platform extend from software developers to business technologists, and now AI users, who, he says, may be looking for a Model Context Protocol (MCP) endpoint.
Such know-how captured in a self-service developer portal enables users – whether they are software developers, or business users using low-code or no-code tooling – to connect AI with existing enterprise IT systems.
Enter Backstage
One platform that seems to have captured the minds of the developer community when it comes to developer self-service is Backstage. Having begun life internally at audio streaming site Spotify, Backstage is now an open source project managed by the Cloud Native Computing Foundation (CNCF).
While many teams that implemented Backstage assumed that it would be an easy, free addition to their DevOps practices, that isn’t always the case. Backstage can be complex and requires engineering expertise to assemble, build and deploy Christopher Condo and Lauren Alexander, Forrester
Pia Nilsson, senior director of engineering at the streaming service, says: “At Spotify, we’ve learned that enabling developer self-service begins with standardisation. Traditional centralised processes create bottlenecks, but complete decentralisation can lead to chaos. The key is finding the middle ground – standardisation through design, where automation and clear workflows replace manual oversight.”
Used by two million developers, Backstage is an open source framework for building internal developer portals. Nilsson says Backstage provides a single, consistent entry point for all development activities – tools, services, documentation and data. She says this means “developers can move quickly while staying aligned with organisational standards”.
Nilsson points out that standardising the fleet of components that comprise an enterprise technology stack is sometimes regarded as a large migration effort, moving everyone onto a single version or consolidating products into one. However, she says: “While that’s a critical part of standardising the fleet, it’s even more important to figure out the intrinsic motivator for the organisation to keep it streamlined and learn to ‘self-heal’ tech fragmentation.”
According to Nilsson, this is why it is important to integrate all in-house-built tools, as well as all the developer tools the business has purchased, in the same IDP. Doing so, she notes, makes it very easy to spot duplication. “Engineers will only use what they enjoy using, and we usually enjoy using the stuff we built ourselves because it’s exactly what we need,” she says.
The fact that Backstage is a framework is something IT leaders need to consider. In a recent blog post, Forrester analysts Christopher Condo and Lauren Alexander warned that most IDPs are frameworks that require assembly: “While many teams that implemented Backstage assumed that it would be an easy, free addition to their DevOps practices, that isn’t always the case. Backstage can be complex and requires engineering expertise to assemble, build and deploy.”
However, Forrester also notes that commercial IDP options are now available that include an orchestration layer on top of Backstage. These offer another option that may be a better fit for some organisations.
AI in an IDP
As well as the assembly organisations will need to carry out if they do not buy a commercial IDP, AI is revolutionising software development, and its impact needs to be taken into account in any decisions made around developer self-service and IDP.
Spotify’s Nilsson believes it is important for IT leaders to figure out how to support AI tooling usage in the most impactful way for their company.
“Today, there is both a risk to not leveraging enough AI tools or having it very unevenly spread across the company, as well as the risk that some teams give in to the vibes and release low-quality code to production,” she says.
According to Nilsson, this is why the IT team responsible for the IDP needs to drive up the adoption of these tools and evaluate the impact over time. “At Spotify, we drive broad AI adoption through education and hack weeks, which we promote through our product Skill Exchange. We also help engineers use context-aware agentic tools,” she adds.
Looking ahead
In terms of AI tooling, an example of how developer self-service could evolve is the direction of travel SAP looks to be taking with its Joule AI copilot tool.
When structure, automation and visibility are built into the developer experience, you replace bottlenecks with flow and create an environment where teams can innovate quickly, confidently and responsibly Pia Nilsson, Spotify
CCS Insights’ Rotibi believes the trend to integrate AI into developer tools and platforms is an area of opportunity for developer self-service platforms. Among the interesting topics Rotibi saw at the recent SAP TechEd conference in Berlin was the use of AI in SAP Joule.
SAP announced new AI assistants in Joule, which it said are able to coordinate multiple agents across workflows, departments and applications. According to SAP, these assistants plan, initiate and complete complex tasks spanning finance, supply chain, HR and beyond.
“SAP Joule is an AI interface. It’s a bit more than just a chatbot. It is also a workbench,” says Rotibi. Given that Joule has access to the SAP product suite, she notes that, as well as providing access, Joule understands the products. “It knows all the features and functions SAP has worked on, and, behind the scenes, uses the best data model to get the data points the user wants,” she says.
Recognising that enterprise software developers will want to build their own applications and create their own integration between different pieces of software, she says SAP Joule effectively plays the role of a developer self-service portal for the SAP product suite.
Besides what comes next with AI-powered functionality, there are numerous benefits in offering developer self-service to improve the overall developer experience, but there needs to be structure and standards.
Nilsson says: “When structure, automation and visibility are built into the developer experience, you replace bottlenecks with flow and create an environment where teams can innovate quickly, confidently and responsibly.”
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