Consider yourself lucky if you have a toilet at your home, because one in three people worldwide, that’s 2.4 billion people globally, have no access to modern sanitation facilities. Of these 2.4 billion, an astonishing 946 million people defecate in the open. Open defecation is threatening survival rates and other health measurements of children living in rural areas of developing countries. In this lightning talk, I’ll describe a game-based approach to addressing this challenging public health issue.
Doo Doo Dash is a simple, single-player mobile game that teaches kids (ages 6-9) the health dangers associated with exposure to feces, and the importance of using toilet facilities for defecation. The message of the game is simple: open defecation is bad; it makes people sick. The game ensures long-term behavior change by addressing psychological principles in the Theory of Planned Behavior. Want to learn more about Doo Doo Dash and how you can design for social change? Come to this lightning talk, where we will discuss the game in detail to inspire a larger conversation around designing for social impact.
As design services begin to penetrate more complex industries than every before, the need to design with regulators has never been higher. In the ten minute talk, I’ll lay out some strategies for designing a product embroiled in complicated legal requirements.
Does your AI have a female voice, like Apple’s Siri or Amazon’s Alexa? If so, does she talk like a woman? Should she? Psychologists have analyzed large bodies of text in the world and discovered that men and women use “function words,” such as pronouns, articles, and prepositions, in significantly different ways. The data consistently show that women use I-words (I, me, my) about 12% more often than men. Men use articles (a, an, the) more than women. Women use “cognitive” words (understand, know, think) as well as “social” words (words that relate to other human beings) more than men. Men use more nouns and women use more verbs. It is important for developers of verbal user interfaces to know about these findings because it is in their hands whether AI personalities perpetuate these differences in language use. On the one hand, doing so might make your “Alexa” seem fractionally more real. On the other, however, replicating these patterns in the language of AIs might serve to perpetuate gender inequalities, in society and in the new forms of human-machine relationships that are emerging today.