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“Babel Fish: “Arthur Dent commented only ‘Eurgh!’ when first inserting

the fish into his ear. It enabled him to understand Vogon Poetry—not necessarily a good thing”. The Hitchhiker’s Guide to the Galaxy, Douglas GS-1101 nmr Adams. Introduction

We rely on common systems and quantitative signals (e.g., price, temperature, food calories) to support everyday decisions. Timely decisions are made, not with precise measures, but with familiarity and suitable approximations. Such quantitative intuition about sustainability is, for the most part, absent. There is a glaring void in our ability to quantify and capture the impact of our actions on sustainability. Although separate data streams are measured with increasing granularity, we do not have a way to grasp quantitatively the impact across different domains—e.g., Arachidonate 15-lipoxygenase driving a car, heating a house, running an air conditioner or watering a lawn. Whether it is in formulating national policy, corporate Staurosporine strategy, or individual actions, we are muddling through a fog. This gap is not adequately filled with CO2 accounting. While CO2 addresses climate change, it is difficult to measure, does not provide quantitative intuition, and has also become a divisive issue that hinders the coalescence of political support. These concerns have

been noted by many, including Mackay (2009), who used basic physics principles to establish a per capita estimate of energy use to quantify sustainability. Having a quantifiable measure is only step one. In order to influence decisions, the measure must be readily observed and interpreted. Van Houwelingen and Van Raaiji 1989) reported that visual monitoring of energy expenses improves energy conservation by more than 12 %, but it persists only as long as the visual reminder is intact. In a recent study, Attari (2010) demonstrated that there is a gap between reality and perception even when limited to decisions involving a single type of energy like electricity used to operate lights and appliances. It adds to a growing literature demonstrating the value of feedback, preferably visual, in a broader decision-making context to motivate behavior leading to energy efficiency (Allcott 2010; Ariely 2008). The unmet need is for a visual, quantitative, and actionable system that can support decisions.