Development is fundamentally about understanding people, their motivations, behaviors and reactions. We have two primary means of understanding people — observing what they do, and what they say. As the AI4D community has noted, people's increased use of mobile devices has led to a wealth of new data relevant to these topics. We are on the cusp of developing incredibly powerful tools that can help us understand how human beings migrate, transact and acquire wealth. This could have a large impact on how we determine policies and allocate resources. Most of this analysis has tended to focus on what people do — where they go, who they talk to, what they buy, etc. I argue that what people say is an equally rich source of development data, often containing information that cannot be obtained from people's actions, such as their needs, hopes and aspirations. Voice is the most natural form of communication, especially for people who speak a non-mainstream language, and/or have marginal literacy skills.  These are often exactly those populations who are most disenfranchised, and therefore most need their voices to be heard.

But whereas in the general Rwandan populace males tend Despite the increasing ubiquity of mobile phones in the developing to be much better educated (76.3% of males are literate, but world, remarkably little is known about the structure only 64.7% of females), among mobile phone users it is the and demographics of the mobile phone market. While a women who achieve higher levels of education: the median few qualitative studies have detailed social norms of phone woman completes secondary school, while the median man use in specific communities (Donner 2007; Burrell 2009), does not (t 4.79). Table 1 shows a few statistics on asset and a handful of quantitative researchers have begun to analyze ownership, with associated sampling error.

The mobile Internet represents a massive opportunity for mobile operators and content providers. Today there are more than 2 billion mobile subscribers, with 3 billion predicted by the end of 2007. However, despite significant improvements in handsets, infrastructure, content, and charging models, mobile users are still struggling to access and locate relevant content and services. An important part of this so-called content-discovery problem relates to the navigation effort that users must invest in browsing and searching for mobile content. In this article we describe one successfully deployed solution, which uses personalization technology to profile subscriber interests in order to automatically adapt mobile portals to their learned preferences. We present summary results, from our deployment experiences with more than 40 mobile operators and millions of subscribers around the world, which demonstrate how this solution can have a significant impact on portal usability, subscriber usage, and mobile operator revenues.

Many applications rely on the device maintaining a replica of a data-structure which is stored on a server, for example news databases, calendars and email.

Many applications rely on the device maintaining a replica of a data-structure which is stored on a server, for example news databases, calendars and email.

Many applications rely on the device maintaining a replica of a data-structure which is stored on a server, for example newsdatabases, calendars and email.

The operation of a human organization requires dozens of everyday tasks to ensure coherence in organizational activities, monitor the status of such activities, gather information relevant to the organization, keep everyone in the organization informed, and so on. Based on this vision, this article reports on ELECTRIC ELVES, a system that has been operational 24 hours a day, 7 days a week at our research institute since 1 June 2000. Tied to individual user workstations, fax machines, voice, and mobile devices such as cell phones and palm pilots, ELECTRIC ELVES has assisted us in routine tasks, such as rescheduling meetings, selecting presenters for research meetings, tracking people's locations, organizing lunch meetings, and so on. We also report the results of deploying ELECTRIC ELVES in our own research organization.

The interdisciplinary makeup allowed for an expansion of the scope of Glymour's One notable extension was the move from android epistemology to android ethics. "they can know everything we know Margaret Boden presented her work Hayes and Ford were responding Participation was limited to 40 If the first two workshops on to the debate in Scientific American researchers selected from several disciplines human and machine cognition are (January 1990) between Searle and (principally computer science, representative, these meetings will the Churchlands about whether a philosophy, and psychology); become hotbeds of constructive and machine could think. Ironically, although this approach makes for much-needed debate. They focus on from the perspective of Hayes and stimulating discussion, it has resulted the foundational and methodological Ford, Searle and the Churchlands are in a competitive review process concerns of those who want to forge essentially in agreement, diverging (about a 10-percent acceptance rate). It is just a theories about the necessary in U.S. politics, the theme of the fact of life that there isn't much material basis (biological versus parallel) Second International Workshop on agreement about methodology and for intelligence. They both Human and Machine Cognition was, foundational issues within these two make specific implementation features What do androids know, and when fields. The positions covered One feature of the workshop that for intelligence. As might be expected, a wide range: "They can know facilitated and, at times, obstructed Paul Churchland objected to this only what androids can know: Android fruitful discussion was its highly interdisciplinary grouping.