At the heart of conservation are the field staff who study and monitor ecosystems in challenging environments. Recent advances in AI models raise the question of whether LLM assistants could improve the experience of data collection for these staff. However, on-device AI deployment for conservation field work poses significant challenges, and is understudied. To address this gap, we conducted semi-structured interviews, surveys, and participant observation with partner conservancies in the Pacific Northwest and Namibia to better understand the field work context. We employ speculative methods through the lens of technology acceptance theory to critically analyze how on-device AI would affect field work, by developing an on-device transcription-language model pipeline, which we built atop of EarthRanger, a widely-used, open-source conservation platform. Our findings suggest that although on-device LLMs hold some promise for field work, the infrastructure required by current on-device models clashes with the reality of resource-limited conservation settings.

We present the design, preliminary deployment, and user evaluation of a Large Language Model (LLM)-based tool to improve privacy in online communications within grassroots and frontline service-providing community organizations that interact with clients as a part of their work. During coordination and service provision, personally identifiable information (PII) may be shared between workers, volunteers, and clients. Collaborating with the Seattle Community Network (SCN) volunteer organization, we built a tool that automatically redacts PII from client coordination messages shared in their public chat server, and reveals the PII only to authorized users upon request. User feedback on this early iteration reveals a high valuing of its privacy-preserving functions, but concerns around trusting LLM output, a requirement to self-host LLMs even on limited hardware, and potential frictions around redaction time and tool onboarding.

Collaboration and community building are crucial for equitable participation in research, especially in disability and accessibility research fields.Engaging with communities of disabled individuals helps understand their unique challenges, expectations, and needs, which should be reflected in assistive technology design.However, a gap exists between research in resource-rich societies and the practices of low-resource settings, where socio-economic and infrastructural constraints are often overlooked.Conversely, the innovation and sustainable solutions in these settings are often

Networking research often abstracts away the people who build, operate, and experience the Internet. Yet, human decisions shape what gets measured, which problems are prioritized, and how solutions are deployed. This paper argues that such human influence is foundational and deserves methodological attention. To do so, we discuss three well-known qualitative methods and approaches: participatory action research, ethnographic methods, and positionality as concrete ways of engaging with the social and operational realities that underlie technical systems. These approaches formalize processes that are commonly implicit in networking research, help surface questions that cannot be answered with traces alone, and make space for voices often left out of the research pipeline or are inadvertently concealed due to the lack of formal procedures to include them in our research methods. Ultimately, we argue for a broader understanding of legitimate, and sometimes informal, contributions to networking research—one that better reflects the human element of how the Internet is structured and is experienced.

No abstract available.

In tiny house villages (THVs), land ownership, local regulations such as zoning, and management frameworks affect how formerly unhoused residents can leverage and augment their built infrastructure with ''smart'' technologies. These dynamics influence THV residents' lived experiences, creating both constraints and opportunities for deploying networked sensors in support of communication, physical security, and shared governance. Through a series of participatory design (PD) workshops and visits with residents of two villages, we identified how residents balance privacy and security concerns when considering Internet-of-Things (IoT) sensor design and deployment. We find, for example, that residents impose constraints on designed sensors for the group's protection, such as a strict ban on camera-based visual or audio surveillance and a preference for local as opposed to cloud data storage. They also identify opportunities for diverse sensors and actuators to improve village accessibility and to alleviate resource sharing tensions. Meanwhile, differences between public and private land ownership directly impact the regulation and infrastructure possibilities for THVs, and historical and current zoning of land shapes the social problems that the community must navigate. Our findings deepen the CSCW research agenda by examining parameters for successful ''smart'' and data-driven technology interventions among low-resourced urban groups experiencing housing precarity and homelessness.

We present dAuth, an approach to device authentication in private cellular networks which refactors the responsibilities of authentication to enable multiple small private cellular networks to federate together to provide a more reliable and resilient service than could be achieved on their own. dAuth is designed to be backwards compatible with off-the-shelf 4G and 5G cellular devices and can be incrementally deployed today. It uses cryptographic secret sharing and a division of concerns between sensitive data stored with backup networks and non-sensitive public directory data to securely scale authentication across multiple redundant nodes operating among different and untrusted organizations. Specifically, it allows a collection of pre-configured backup networks to authenticate users on behalf of their home network while the home network is unavailable. We evaluate dAuth's performance with production equipment from an active federated community network, finding that it is able to work with existing systems. We follow this with an evaluation using a simulated 5G RAN and find that it performs comparably to a standalone cloud-based 5G core at low load, and outperforms a centralized core at high load due to its innate load-sharing properties.

This paper presents a mixed-methods study of app-based motorcycle taxis in Thailand to explore the social dynamics of rideshare drivers and their exercised autonomy both through social pressure and a hostile work environment. As motorcycle taxis are open-air vehicles, drivers can be exposed to prolonged air pollution and other weather events, potentially impacting their health. In an initial quantitative study of server-side rideshare logs, we unexpectedly found that drivers do not exercise the autonomy provided by their rideshare platform to avoid air pollution events. This prompted a follow-on investigation through semi-structured interviews of both drivers and passengers in three provinces to explore why these drivers fail to experience the autonomy promised by gig-work in this context and elucidated further examples this lack of autonomy experienced by drivers. Our study sheds light on the social context that may constrain a driver's agency, including financial pressures, weather conditions, conflicts with local taxi organizations, and a false perception that drivers need to work around the ride assignment algorithm to avoid being blacklisted. We find that when leveraging app-based rideshare opportunities, drivers simultaneously perceive increased flexibility in their work hours and a lack of agency to prioritize their health and safety. We conclude with a discussion on potential interventions aimed at mitigating the forces preventing drivers from exercising their autonomy.

The use of blockchain in regulatory ecosystems is a promising approach to address challenges of compliance among mutually untrusted entities. In this work, we consider applications of blockchain technologies in telecom regulations. In particular, we address growing concerns around Unsolicited Commercial Communication (UCC aka. spam) sent through text messages (SMS) and phone calls in India. Despite several regulatory measures taken to curb the menace of spam it continues to be a nuisance to subscribers while posing challenges to telecom operators and regulators alike.

Connection coalescing, enabled by HTTP/2, permits a client to use an existing connection to request additional resources at the connected hostname. The potential for requests to be coalesced is hindered by the practice of domain sharding introduced by HTTP/1.1, because subresources are scattered across subdomains in an effort to improve performance with additional connections. When this happens, HTTP/2 clients invoke additional DNS queries and new connections to retrieve content that is available at the same server. ORIGIN Frame is an HTTP/2 extension that can be used by servers to inform clients about other domains that are reachable on the same connection. Despite being proposed by content delivery network (CDN) operators and standardized by the IETF in 2018, the extension has no known server implementation and is supported by only one browser. In this paper, we collect and characterize a large dataset. We use that dataset to model connection coalescing and identify a least-effort set of certificate changes that maximize opportunities for clients to coalesce. We then implemented and deployed ORIGIN Frame support at a large CDN. To evaluate and validate our modeling at scale, 5000 certificates were reissued. Passive measurements were conducted on production traffic over two weeks, during which we also actively measured on the 5000 domains.

With this poster we present an initial analysis of the implications of the COVID-19 pandemic and regional lockdowns on Internet traffic and credit transfers within a rural community network in Bokondini, Indonesia. We find initial evidence that phenomena observed in other large-scale datasets around lockdowns did not occur in this context, with little change observed in network utilization. We do find a marginal increase in the frequency and size of transfers in the network and observe some users accessing health information and using health-related applications.

Interactive wildlife-tracking maps on public-facing websites and apps have become a popular way to share scientific data with the public as more conservationists and wildlife researchers deploy tracking devices on animals. Environmental organizations engage with the public for a variety of reasons: to raise awareness of environmental causes, build relationships with potential partners, and encourage people to take political and personal actions. However while there is a large body of work comparing different media strategies for environmental communication goals, the effectiveness of interactive data visualizations for these purposes remains unclear. This work examines the strengths and weaknesses of interactive wildlife-tracking maps for environmental communication. We interview conservationists about their aspirations for using these maps with their own data, and conduct a study gauging lay users’ reactions to different designs. Many conservationists aspire to create deep, immersive user engagements with these maps—letting users relate to data-driven stories about individual animals and freely explore the nuances of the tracking data. Our findings show potential for the most highly-motivated users to deeply engage with these data and stories, but more casually-interested audiences struggle with the maps’ complexities. However for casual audiences, wildlife tracking maps can still superficially but effectively showcase the organizations’ work to protect the species; perhaps inspiring hope for their future, attracting audiences to other communication channels to learn more, and adding to the organizations’ credibility. Following these insights, we present a set of design considerations for further development of similar wildlife-tracking map applications; emphasizing their needs for user onboarding, context for data interpretation, and integration with relatable media.

While only generating a minuscule percentage of global traffic, largely lost in the noise of large-scale analyses, remote rural networks are the physical frontier of the Internet today. Through tight integration with a local operator’s infrastructure, we gather a unique dataset to characterize and report a year of interaction between finances, utilization, and performance of a novel, remote, data-only Community LTE Network in Bokondini, Indonesia. With visibility to drill down to individual users, we find use highly unbalanced and the network supported by only a handful of relatively heavy consumers. 45% of users are offline more days than online, and the median user consumes only 77 MB per day online and 36 MB per day on average, limiting consumption by frequently “topping up” in small amounts. Outside video and social media, messaging and IP calling provided by over-the-top services like Facebook Messenger, QQ, and WhatsApp comprise a relatively large percentage of traffic consistently across both heavy and light users. Our analysis shows that Internet-only Community Cellular Networks can be profitable despite most users spending less than $1 USD/day, and offers insights into the unique properties of these networks.

Congestion control mechanisms, by which network users share constrained capacity on Internet links, are heavily studied in computer science. Such mechanisms are traditionally automated, assuming that users do not wish to be involved in addressing congestion. However, in community-owned and operated networks, users have control over daily operational choices. We explore the design of community-based congestion policies and mechanisms, through the lens of network capacity as a Common Pool Resource (CPR). Through a series of workshops and interviews in a rural community in Oaxaca, Mexico, we encounter design opportunities for new types of tools supporting communal network management. Participants expressed desires for preserving individual privacy while collecting longitudinal data to track the network's impact on the community, prioritization of high-value applications, equal link sharing between users, and human-mediated congestion management in lieu of automated enforcement. We report qualitative insights and offer design directions for future systems to address network resources in a manner compatible with Ostrom's principles for CPR governance.

Abstract The Internet’s Domain Name System (DNS) responds to client hostname queries with corresponding IP addresses and records. Traditional DNS is unencrypted and leaks user information to on-lookers. Recent efforts to secure DNS using DNS over TLS (DoT) and DNS over HTTPS (DoH) have been gaining traction, ostensibly protecting DNS messages from third parties. However, the small number of available public large-scale DoT and DoH resolvers has reinforced DNS privacy concerns, specifically that DNS operators could use query contents and client IP addresses to link activities with identities. Oblivious DNS over HTTPS (ODoH) safeguards against these problems. In this paper we implement and deploy interoperable instantiations of the protocol, construct a corresponding formal model and analysis, and evaluate the protocols’ performance with wide-scale measurements. Results suggest that ODoH is a practical privacy-enhancing replacement for DNS.

Wildlife conservancies across the globe are increasingly recognizing their need to support their surrounding communities to sustainably operate. Rapidly shifting environmental and sociopolitical climates increasingly stress existing resource and service provisions, forcing wildlife conservancies to co-manage with local communities shared resources like water, wildlife, soil, pollinators, and security. This work presents a case study in Laikipia, Kenya on Ol Pejeta Conservancy's use of text-based technologies to provide services and build relationships with the many widely-dispersed communities on its borders. Through technology deployments, staff interviews, and community focus groups, we investigate a potential role for basic mobile phone services, like SMS and USSD, to help conservancy personnel disseminate accurate and timely information, gather community feedback, address grievances, and improve accountability. Our findings show that communication with locals requires intense and ongoing effort from conservancy staff. Partially successful deployments of phone services provide a proof-of-concept for their utility in community relations but highlight particular design challenges for wildlife conservancies; having critical needs for broad inclusive engagement; clear, deliberate communication; and careful trust-building.

What determines the success of community cellular networks? We leverage unique circumstances where all households in seven localities were interviewed before the launch of cellular networks. We observed substantial differences in network adoption across communities. Four communities displayed high and regular usage, while usage dissipated shortly after the network launch in three sites. Sixty-five percent of households made or received at least one call or text message. We find that a one standard deviation increase in household wealth is correlated with a three percentage point increase in network adoption and 43 additional cellular network transactions. Agricultural households were ten percentage points more likely to adopt the network than other households and female-headed households were five percentage points more likely to use the network at least once.

Across the world, government websites are expected to be reliable sources of information, regardless of their view count. Interactions with these websites often contain sensitive information, such as identity, medical, or legal data, whose integrity must be protected for citizens to remain safe. To better understand the government website ecosystem, we measure the adoption of https including the "long tail" of government websites around the world, which are typically not captured in the top-million datasets used for such studies. We identify and measure major categories and frequencies of https adoption errors, including misconfiguration of certificates via expiration, reuse of keys and serial numbers between unrelated government departments, use of insecure cryptographic protocols and keys, and untrustworthy root Certificate Authorities (CAs). Finally, we observe an overall lower https rate and a steeper dropoff with descending popularity among government sites compared to the commercial websites & provide recommendations to improve the usage of https in governments worldwide.

Recent work has applied machine learning methods to automatically find and/or assess pedestrian infrastructure in online map imagery (e.g., satellite photos, streetscape panoramas). While promising, these methods have been limited by two interrelated issues: small training sets and the choice of machine learning model. In this paper, aided by the recently released Project Sidewalk dataset of 300,000+ image-based sidewalk accessibility labels, we present the first examination of deep learning to automatically assess sidewalks in Google Street View (GSV) panoramas. Specifically, we investigate two application areas: automatically validating crowdsourced labels and automatically labeling sidewalk accessibility issues. For both tasks, we introduce and use a residual neural network (ResNet) modified to support both image and non-image (contextual) features (e.g., geography). We present an analysis of performance, the effect of our non-image features and training set size, and cross-city generalizability. Our results significantly improve on prior automated methods and, in some cases, meet or exceed human labeling performance.

SMS fraud has become a growing concern for those working toward financial inclusion, however, it is often unclear how widespread such threats are in practice. This multi-method study investigates SMS fraud in Pakistan through identification and categorization of fraudulent messages as well as the impact on those who receive such messages. We collect fraudulent SMS messages by various means, including byway of a custom-built Android smartphone application. To complement this, we interview people exposed to SMS fraud and representatives of mobile network operators. Based on our analysis, lottery type fraud schemes dominate SMS fraud in Pakistan, and these schemes have the greatest impact on vulnerable low-income, rural populations. We offer a simple heuristic for fraud detection that has a high accuracy rate and is adaptable to evolving fraud schemes, and conclude with a recommendation for a fraud mitigation strategy to target fraudster call back numbers.

Agricultural market information (MI) services provide smallholder farmers with convenient access to price information and have demonstrated potential to improve their incomes. Some recent evaluations of MI systems, however, have shown disappointing results and brought forth many complicating factors. Cautious of the mixed literature, we investigate the potential effectiveness and likely limitations of an MI service for improving livelihoods of smallholder farmers in the context of Loop, a shared transport-to-market-service for farmers. We conducted interviews with 17 farmers and 3 commission agents in Buxar, Bihar (India). Consistent with "information scarcity" and "information asymmetry" theories, we report how many farmers in this area regularly use mobile phones to check prices for choosing markets and negotiating transactions. Participants reported increases in the numbers of traders and price stabilization since the arrival of mobile phones. However, we found many other diverse factors that often outweigh the importance of market prices and inhibit market access, including market capacity, time, unfamiliarity with new markets, personal relationships, attitudes towards risk, credit relationships, and physical danger. Finally, to probe which of these additional factors might be addressable using an MI service, we present exploratory findings from preliminary user-interface studies.

In this paper we introduce CoLTE, a solution for LTE-based community networks. CoLTE is a lightweight, Internet-only LTE core network (EPC) designed to facilitate the deployment and operation of small-scale, community owned and operated LTE networks in rural areas with limited and unreliable backhaul. The key differentiator of CoLTE, when compared to existing LTE solutions, is that in CoLTE the EPC is designed to be located in the field and deployed alongside a small number of cellular radios (eNodeBs), as opposed to the centralized model seen in large-scale telecom networks. We also provide performance results and lessons learned from a real-world CoLTE network deployed in rural Indonesia. This network has been sustainably operating for over six months, currently serves over 40 active users, and provides measured backhaul reductions of up to 45% when compared to cloud-core solutions.

We will introduce and demonstrate CoLTE, an all-in-one solution for LTE-based community networks. CoLTE is a lightweight, Internet-only LTE core network (EPC) based on OpenAirInterface. CoLTE is designed to facilitate the deployment and operation of small-scale, community owned and operated LTE networks, with a particular eye towards expanding Internet access into rural areas with limited and unreliable backhaul. CoLTE comes paired with a basic, IP-based network manager called Haulage, as well as basic locally-hosted webservices. The key differentiator of CoLTE, when compared to existing LTE solutions, is that in CoLTE the EPC is designed to be located in the field and deployed alongside a small number of cellular radios (eNodeBs), as opposed to the centralized model seen in large-scale telecom networks.

This paper analyzes the processes and challenges of technology repair in remote, low-income areas far from standard ICT repair infrastructure. Our sites of study are the fishing and farming villages of Dibut, Diotorin, and Dikapinisan in Aurora Province, Philippines, located in coastal coves against a mountain range. Residents are geographically isolated from urban areas, with the nearest peri-urban center of Baler a boat trip of several hours away, infeasible in some sea conditions. Unlike prior work in more connected rural areas, there are no local repair shops and device repair is uncommon, despite frequent breakage due to harsh conditions for electronics. The scarcity of local electronics repair limits technology access and leads to accumulation of e-waste. While prior work demonstrates that local electronics repair capability does arise in many rural areas around the world, we must also acknowledge that the successful emergence of this infrastructure depends on the intersection of many structural conditions and cannot be taken for granted. We present the material hardships of achieving local repair in terms of seams between heterogeneous urban and rural infrastructures, which illustrate the cove communities' marginality with respect to many forms of public infrastructure. However, intermittent and informal repair infrastructures based on trust relationships emerge to patch these seams in remote settings. We show how trust affects the way people dynamically construct repair infrastructure and why, based on their remoteness and the resulting value propositions of repair. Networks of trust between repairers, their clients, suppliers, fellow repairers, and certifying or training institutions crucially facilitate the movement of resources and expertise across the Philippines, but also reinforce the marginality of residents and repairers in the coves. Despite these structural challenges, local people are able to maintain a robust ecosystem for rural electrical line repair, from which we generalize the model of training grounds as a strategy for sustaining local communities of repair experts.

Repair and maintenance requirements limit the successful operation of rural infrastructure. Current best practices are centralized management, which requires travel from urban areas and is prohibitively expensive, or intensively training community members, which limits scaling. We explore an alternative model: crowdsourcing repair from the community. Leveraging a Community Cellular Network in the remote Philippines, we sent SMS to all active network subscribers (n = 63) requesting technical support. From the pool of physical respondents, we explored their ability to repair through mock failures and conducted semi-structured interviews about their experiences with repair. We learned that community members would be eager to practice repair if allowed, would network to recruit more expertise, and seemingly have the collective capacity to resolve some common failures. They are most successful when repairs map directly to their lived experiences. We suggest infrastructure design considerations that could make repairs more tractable and argue for an inclusive approach.

Phone-based mobile money is becoming the dominant paradigm for financial services in the developing world. For example, mPesa has a cash flow of over thirty billion USD, equivalent to nearly half of Kenya's GDP. Inside of these markets, competitors have appeared who leverage ThinSIMS, small SIM-card add-ons, to provide alternative mobile money implementations. However, the security implications of ThinSIMs are not well understood.

The radio interfaces and network architectures of WiFi and cellular systems are converging along many dimensions. While both systems are largely adopting the centralized architecture of traditional cellular deployments, this design comes with fundamental disadvantages that limit how these networks grow and develop. As a response, we present Distributed LTE (dLTE), an architecture offering the high radio performance of licensed and coordinated waveforms as well as the openness to organic expansion and growth of traditional WiFi. We challenge the assumption that good performance requires a centralized packet processing core, and propose hybrid approaches to coordination that prioritize system openness. We argue that dLTE is a particularly good fit for rural areas, where the LTE waveform is more appropriate than WiFi, yet it is uneconomical for centralized providers to deploy traditional cellular systems.

In the last decade, billions of people worldwide have upgraded from basic 2G feature phones to data-enabled 4G smartphones. In most cases, people upgrade in areas with 4G coverage (typically cities and large towns), but increasingly, people choose to upgrade in areas that only have 2G coverage or no cellular coverage at all. This counterintuitive behavior -- upgrading your phone despite living in an area that does not actively support many of the features of that new device -- is the focus of this work.

The smartphone has been touted as the technology of the 21st century. Global smartphone adoption rates are growing rapidly, up to over 24% in 2014, with usage increasing 25% in the last year. However, rural areas are often the last places to benefit from these technological trends. Utilizing cellular network registration logs, we explore the adoption and usage of smartphones in an extremely remote community in Indonesia. We found that 16% of the phones in the area were smartphones (compared to between 14--24% in Indonesia). This shows that smartphone adoption in rural Indonesia is similar to the rest of the country. We also explored usage in the network, and found that smartphone users were more likely to text, especially to other smartphone users.

Over five billion people are active cellular subscribers, spending over a trillion dollars a year on communications. Despite this, hundreds of millions of people are still not connected.

Online labor markets, such as Amazon's Mechanical Turk, have been used to crowdsource simple, short tasks like image labeling and transcription. However, expert knowledge is often lacking in such markets, making it impossible to complete certain classes of tasks. In this work we introduce an alternative mechanism for crowdsourcing tasks that require specialized knowledge or skill: communitysourcing --- the use of physical kiosks to elicit work from specific populations. We investigate the potential of communitysourcing by designing, implementing and evaluating Umati: the communitysourcing vending machine. Umati allows users to earn credits by performing tasks using a touchscreen attached to the machine. Physical rewards (in this case, snacks) are dispensed through traditional vending mechanics. We evaluated whether communitysourcing can accomplish expert work by using Umati to grade Computer Science exams. We placed Umati in a university Computer Science building, targeting students with grading tasks for snacks. Over one week, 328 unique users (302 of whom were students) completed 7771 tasks (7240 by students). 80% of users had never participated in a crowdsourcing market before. We found that Umati was able to grade exams with 2% higher accuracy (at the same price) or at 33% lower cost (at equivalent accuracy) than traditional single-expert grading. Mechanical Turk workers had no success grading the same exams. These results indicate that communitysourcing can successfully elicit high-quality expert work from specific communities.

Many children, especially in the developing world, must share a computer at school. Often, more advanced or aggressive students dominate, leaving others frustrated and disengaged. One promising approach is to provide each student with their own input device, usually a mouse, while sharing a common computer and display. Previous multiple mouse sharing efforts for education have relied on developing custom applications that encourage collaboration --- for example, by requiring that all users click on an icon or option to proceed. Implementing this requires access to application source code, which is unlikely to be available, and would require significant engineering effort to adapt even if it was. To address these limitations, we developed Metamouse. Metamouse only conveys clicks to the application when users have already agreed on a screen location, within a pre-defined tolerance (a novel sharing technique that we call "location-voting") and requires no access to the application source code. We have implemented two versions of location-voting --- one that requires all users to agree ("Consensus"), and another where only a majority is required ("Majority"). To evaluate Metamouse, we conducted a user study with 24 fifth-grade students in a low-income school in Bangalore, India. Our results demonstrate that Metamouse is intuitive, usable and has the potential to outperform other sharing strategies in terms of user engagement, generating discussion, and overall satisfaction. We also show that the Majority approach provides all of these benefits as effectively as Consensus with less frustration for faster users and less embarrassment for slower ones.

Traditional Single Display Groupware (SDG) solutions have been used to create software for developing regions. SDG allows for greater utilization of the limited infrastructure available in such areas. This technology is particularly appropriate in classrooms where groups of children often use educational software on a single computer. However, SDG has faced several challenges working with legacy applications. Our technology, called metamouse, takes a step toward an integrated multi-user application by allowing users to collaborate within unmodified legacy educational software.

How should players bid in keyword auctions such as those used by Google, Yahoo! and MSN?allWe consider greedy bidding strategies for a repeated auction on a single keyword, where in each round, each player chooses some optimal bid for the next round, assuming that the other players merely repeat their previous bid. We study the revenue, convergence and robustness properties of such strategies. Most interesting among these is a strategy we call the balanced bidding strategy (BB): it is known that BB has a unique fixed point with payments identical to those of the VCG mechanism. We show that if all players use the BB strategy and update each round, BB converges when the number of slots is at most 2, but does not always converge for 3 or more slots. On the other hand, we present a simple variant which is guaranteed to converge to the same fixed point for any number of slots. In a model in which only one randomly chosen player updates each round according to the BB strategy, we prove that convergence occurs with probability 1.We complement our theoretical results with empirical studies.