2.0

Chronique

In an electropop project uniquely for the Internet age, producer and remix specialist Alan Wilkis offers big melodies on top of seriously catchy grooves along with distortion and loads of anxiety on his Big Data full-length debut, the technology-themed 2.0. With its proven hit "Dangerous" making appearances in films (including 2014's Veronica Mars and Earth to Echo) and reaching number one on Billboard's Alternative Songs chart several months before the album's release, 2.0 will likely appeal to those who were drawn to the tune's tremendously hooky bassline and chorus, and lyrics about real or imagined surveillance sung by Daniel Armbruster of Joywave ("How could they know/How could they know what I've been thinking?/But they're right inside my head because they know"). Though each of the record's ten tracks features a different vocalist, all are similarly infectious and unsettling. The impressive mix of featured singers includes indie electronic artists White Sea and Twin Shadow, Dragonette, the R&B-influenced Kimbra and Jamie Lidell, indie rockers Bear Hands, and Jenn Wasner of Wye Oak. Most surprisingly, Rivers Cuomo sings lead on "Snowed In" -- wordplay on NSA-surveillance whistleblower Edward Snowden. There's not a hint of Weezer on the tune with its anxiety-filled thumps and authoritarian point of view: "Whistleblowing is an act of aggression/So he better run cuz I'm gonna teach him a lesson." Distorted bass, drums, and guitar; unexpected, prodding keyboard tones; and mechanical noises pepper the dance-inducing tracks, reflecting the creepy unease of similarly disconcerting lyrics delivered by otherwise alluring performances. This contradiction -- being drawn to something simultaneously troubling -- is the theme of the whole album as expressed in lyrics about our complicated and fearful relationship with helpful but invasive connected technologies. In short, this is pretty smart dance music. Besides being well plotted, 2.0's a satisfying full-length affair for those who can handle the needling, decidedly un-ambient sounds and persistent paranoia; it's highly recommended for neurotics, clubbers, and karaoke divas alike, but has the potential to connect broadly as danceable Zeitgeist. So, plug into some Big Data and dance like no one's watching (but someone's probably watching).

© Marcy Donelson /TiVo