跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+1072新增论文
+845其中 AI 相关
+94已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-10 07:06 · 全站最近入库:2026-11-09 13:22各信源进度 →

统计口径与数据新鲜度

统计 2026-11-09 07:12 — 2026-11-10 07:12(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-10 07:06最近发现新增版本:2026-11-09 13:22库内论文最新更新时间:2026-11-07 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

18,172 已收录论文15,506 AI 相关4,527 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 1 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-10 07:04(北京时间)
新论文 · v1arXiv:2611.04820

AI for eGovernance: Leveraging Language Technologies For Digital Inclusion

Cynthia Jayne Amol, Lilian Wanzare

原文摘要

The Kenyan government has invested heavily in the digitisation of public service delivery, in line with the Kenya Digital Master Plan 2022-2032. The national eGovernment platform, eCitizen, hosts services that are vital to citizens' livelihoods, including business registration, youth enterprise lending, digital literacy and tax filing. However, the platform faces digital inclusion challenges that limit equitable access for marginalised groups, particularly youth in rural areas and persons with disabilities. This exclusion is driven by a language barrier, since the platform is primarily in English with limited Swahili support, and by a text-only interface that excludes low-literacy and visually impaired users. This paper reports findings from six one-on-one interviews and an eleven-person roundtable discussion across four platforms essential to youth livelihoods: Ajira Digital, Kenya Revenue Authority (KRA) iTax, Higher Education Loans Board (HELB) and the Youth Enterprise Development Fund (YEDF). Drawing on these findings, on Web Content Accessibility Guidelines (WCAG) 2.1 principles as a design lens for diagnosing eCitizen's accessibility gaps, and on comparator models such as Estonia's Bürokratt and India's Bhashini, the paper proposes a human-centred, systems-minded framework for embedding generative AI and language technologies into eCitizen, including text simplification, neural machine translation, text-to-speech and speech-to-text. The paper argues that, when deployed responsibly with appropriate human oversight, these interventions could meaningfully improve access to government services for linguistically excluded citizens. It also emphasises that AI alone cannot overcome the broader structural barriers, including unemployment and educational inequality, that shape digital exclusion.

cs.HC