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The American anthropologist Edward Fischer, paraphrasing Aristotle, said that the good life is ‘a life worth living’, or a journey towards ‘a fulfilled life’. It has to do with happiness but is not limited to it; it’s often – perhaps counterintuitively – linked to commitment and sacrifice, to the work of becoming a particular person. The French philosopher Michel Foucault in 1982 described these practices as technologies of the self. According to Foucault, the self is ‘not given to us … we have to create ourselves as a work of art’. My informants on the streets of Paris were striving – in their own ways – towards being better selves. I came to understand the activities, processes and routines that they engaged in – begging, making a shelter, accessing temporary housing, etc – as practices of the self geared towards a better life, as practices of homemaking on the street, as practices of hope.

Aside from François, others I met on the streets of Paris – such as Sabal from India, and Alex from Kosovo – talked about their engagement in such practices of hope. Following them through soup kitchens, drop-in centres, government institutions and homeless shelters, I observed two main ways in which they attempted to push for a better life. Both of them were connected to the idea of home: my informants in Paris were longing to find and go back to a homeland, often one from the past, while on a daily basis they were struggling to construct a home in order to survive. That was what a better life looked like for them.

Home, according to the Australian social scientist Shelley Mallett, is always suspended between the ideal and the real. It relates to ‘the activity performed by, with or in person’s things and places. Home is lived in the tension between the given and the chosen, then and now.’ While Sabal’s India was part of the ideal, what Alex was dealing with was closer to the ‘real’ side of this distinction. His home-making efforts were a continuous process of daily activities.

Lyons announced the Partnership on AI’s first three working groups, which are dedicated to fair, transparent, and accountable AI; safety-critical AI; and AI, labor, and the economy. Each group will have a for-profit and nonprofit chair and aim to share its results as widely as possible. Lyons says these groups will be like a “union of concerned scientists.” “A big part of this is on us to really achieve inclusivity,” she says. Tess Posner, the executive director of AI4ALL, a nonprofit that runs summer programs teaching AI to students from underrepresented groups, showed why training a diverse group for the next generation of AI workers is essential. Currently, only 13 percent of AI companies have female CEOs, and less than 3 percent of tenure-track engineering faculty in the US are black. Yet an inclusive workforce may have more ideas and can spot problems with systems before they happen, and diversity can improve the bottom line. Posner pointed out a recent Intel report saying diversity could add $500 billion to the US economy.

“It’s good for business,” she says. These weren’t the first presentations at EmTech Digital by women with ideas on fixing AI. On Monday, Microsoft researcher Timnit Gebru presented examples of bias in current AI systems, and earlier on Tuesday Fast.ai cofounder Rachel Thomas talked about her company’s free deep-learning course and its effort to diversify the overall AI workforce. Even with the current problems achieving diversity, there are more women and people of color that could be brou

ght into the workforce.