Lisa Schirch 25 Spheres of Digital Peacebuilding and PeaceTech 13 The Kenya-based Sisi ni Amani Kenya (SNA-K) uses mobile phone-based technologies to facilitate rapid SMS (text message) communication to promote peace. SNA-K created violence prevention messages by asking communities to use their expertise in developing messages that would resonate with local audiences. SNA-K created civic education messages focusing on voter education to reduce vulnerability to false information rumours about the election process. SNA-K also emphasised calming messages. People forwarded the SNA-K messages on to others, providing election-related information.42 4. Digital Early Warning of Violence and Dangerous Speech Providing an early warning of violent conflict requires collecting diverse sources of data. New technologies enable vast data collection for improved early warning of conflict, with the hope that this can translate into the political will to invest in conflict prevention.43 Early warning indicators include an increase in hate speech, weapons purchases, increased movement of armed groups, and new patterns in the market as rumours spread. Data management systems can obtain early warning data by scraping social media, legacy media, bank transactions, traffic patterns, and troop movements observed through Google Earth, drones, and other monitors. Following Kenya’s use of technology for preventing election violence, Kenyans developed a range of technologies for preventing rumours and violence. Uchaguzi enables users to send an SMS about incidents of violence to the authorities with a toll-free number. The Kenyan government and UNDP launched the Uwiano Platform for Peace in 2010 to provide online tracking tools for citizen reports of violence. Umati uses social media data scraping to monitor hate speech on the internet and offers visual maps of where it is spreading. Una Hakika (‘Are you sure?’) was formed to provide users with a way to verify dangerous rumours using mobile phones following disinformation that led to several massacres and heightened inter-communal tensions in the Tana Delta region.44 PeaceTech Lab maps the local lexicons of hate speech on social media in various languages and regions of the world and aims to empower civil society and tech companies to identify and interrupt the spread of hate speech. The hate speech lexicons identify and explain local jargon, metaphors, and other inflammatory language on social media while offering alternative words and phrases that can be used to combat the spread of hate speech.45 Hate speech almost always is contextually specific. Hate speech becomes “dangerous speech” when it begins to translate to direct physical threats and harms. The Dangerous Speech Project (DSP) provides early warning by monitoring hate speech to determine where and when it becomes dangerous speech that may catalyze intergroup or physical violence. By understanding the characteristics of dangerous speech, DSP explores whether this Seema Shah and Rachel Brown. Programming for Peace: Sisi Ni Amani Kenya and the 2013 Elections. Philadelphia: Center for Global Communication Studies Annenberg School for Communication University of Pennsylvania, 2014. 43 Francesco Mancini, ed. New Technology and the Prevention of Violence and Conflict. New York: International Peace Institute. 2013. 44 Patrick Mutahi and Brian Kimari. “The Impact of Social Media and Digital Technology on Electoral Violence in Kenya.” Institute of Development Studies. No 493. August 2017. 45 See the PeaceTech Lab’s website for more information: https://www.peacetechlab.org/hate-speech 42