The current (November 2014) United States election reminds us that sophisticated data science techniques are employed on the public in attempt to influence opinion and persuade votes. The slick television advertising, debate prevarications, and policy position distortions and exaggerations have soured many citizens on the current state of modern democracy. Indeed, most feel we are not getting the straight scoop - the real positions and policy agendas - and our pool of public candidates and leaders is mediocre at best. The best and brightest avoid public office and it shows.

When Winston Churchill said "The best argument against democracy is a five-minute conversation with the average voter" he likely was referring to low-information voters as well as bad and biased information provided to voters to help them select political leaders and policy goals.

Michael Malak provides great insights in his blog post "Data Science for Reverse Democracy" about the use and misuse of data science by politicians to obtain more votes to win elections.

Brother Malak makes the case that data science today is being misused to invert traditional consent-of-the-governed democratic theory. The way democracy should work is the candidate or political leader states publicly their agendas and policy goals and hope voters ratify those goals in an election. Or an elected official does what he or she wants, then let voters approve or reject. This creates political accountability - vital to the health of democracy.

Yet strong evidence suggests the modern political class has subverted accountability. The way it really works is politicians cloak agendas in some mystery - use data science to tailor different specific messages to different segmented citizens (telling each segment what they want to hear) - then does what they desire anyway, even if a majority of voters reject the agenda disclosed. What this produces is a confused citizenry who have little to no idea what the candidate or political leader really believes and what in fact are the policy goals. As a result the polity finds it difficult, if not impossible, to distinguish political signal from noise.

I suggest this has produced both a cynical electorate and poor quality political leadership from all ideological persuasions. A lethal combination for healthy democracy in need of urgent repair.

What modern democracies need is an ideologically and politically neutral third-party organization that uses data science to distinguish between what politicians disclose and what evidence shows are the real agendas. In other words, help the public separate political signal from noise.

To exercise it's duty as citizens and to keep politicians honest, the public needs an easy to understand data visualization of real agendas and likely predicted coarse(s) of action - so citizens can make an informed public leadership selection - a vote based on reality (signal) and not hype (noise).

Data science has the potential to even the playing field and provide citizens with evidence-based information in the form of data visualizations - in contrast to slick advertisements and marketing - that are simple and informative, allowing voters to understand true agendas and policy goals - as well as achievements and failures based on facts and evidence to hold public leaders accountable.

Furthermore, ideologically and politically neutral data science can distinguish between successful and failed public policies based on facts and evidence and provide findings to both leaders to improve policy and citizens so they can hold leaders accountable and make better policy goal selections.

Modern democracies demand better leaders and higher quality information to make improved political choices for a better future.