Music

"Dirty Computer" - Janelle Monáe ft Brian Wilson, Zoë Kravitz, Grimes, Pharrell Williams [YouTube Full Visual Album]

Monáe's 'emotion picture' celebrates sexuality and individuality
Delia Joyce

by Delia Joyce

Published May 04, 2018

Last week, Janelle Monáe released Dirty Computer, her first album in five years. This time it is accompanied by an "emotion picture" which she defines as a narrative film and accompanying musical album. The science fiction film addresses a wide range of trending social issues like gender equality, police brutality, the impact of technology, and the importance of individuality.

Set in a futuristic dystopian world where all the people are computers, Dirty Computer is a phenomenal work of Afrofuturism — a term coined in 1994 by Mark Dery in his essay, "Black to The Future." Dery defines the concept as “speculative fiction that treats African-American themes and addresses African-American concerns in the context of 20th century technoculture."  Monáe’s film gives a futuristic twist to retro images, such as the 1970s Ford Mustang-like flying cars, and it features a number of phenomenal black artists, including Tessa Thompson, Jayson Aarona, and herself in the leading role of “Jane.”

The core of this film lies in it’s allusion to politics throughout American history. In an interview with New York Magazine's Vulture, Monáe discussed how the most recent presidential election actually sped up the final release of Dirty Computer: "My ancestors literally built the White House that the leader of the free world sleeps in," she explained, "but [Donald Trump] still disrespects immigrants and people who were forced to come over here." The oppression of the "dirty computers" in which the "clean computers" force anyone deemed as "dirty" to undergo intensive memory cleansing is a direct parallel to white colonists forcing people of color into slavery and assimilation.

For years, Monáe has paid homage to her working-class parents and ancestors by dressing herself in black and white — the same color as their work uniforms. The song "Django Jane," features costumes of both bellhop-like suits and butlers as well as black leather jackets, similar to the iconic dress of the civil-rights-era Black Panthers. She wanted to celebrate those who were marginalized and oppressed.

Each song sprinkles classic R&B and funk with the glitter of new-age psychedelic pop.  If you hear the influence of Prince, especially on songs like "Make Me Feel" and "Americans," that is because he was a mentor to Monáe and the two worked together closely on this album. In her latest interview with New York Times, she discussed how Prince’s sudden death in 2016 delayed the release of new music and made her reevaluate how to present herself. “The first songs deal with realizing that this is how society sees me,” she explained, “This is how I’m viewed. I’m a ‘dirty computer,’ it’s clear. I’m going to be pushed to the margins, outside margins, of the world.” She took the label of a "dirty computer" and owned it — reclaiming it as an empowering identity that the world should celebrate, not erase.

So, what inspired the message behind Dirty Computer? "It was us," she said in a recent YouTube Q&A with Ari Fitz, "It was black women, it was my brothers and sisters in the LGBTQIA community, it was immigrants, disabled, it was us, it was all the dirty computers around the world. That was my inspiration." 

Dirty Computer, the album, is available on most major streaming services, as well as Amazon.

Dirty Computer,  the emotion picture, is available on YouTube.  Stream it for free in the player at the top of this page.

Check out Janelle Monáe's Zumic artist page for music, news, and concert tickets.

3
323
artists
Brian Wilson Grimes Janelle Monáe Pharrell Zoë Kravitz
genres
Funk Hip Hop Pop R&B-Soul
сomments
Send Feedback

Hand-Picked Music for Your Taste

Follow artists, discover new music, and personalize your music experience.
JOIN US
Registration and login will only work if you allow cookies. Please check your settings and try again.

OK
Web Analytics