In the 2020 General Election, coming up waaaaay sooner than you think, time being what it is, there are eight (count ’em, eight) Republican Senators who are up for election unopposed. Actually, two of the eight are retiring but, in all cases, whether it’s a replacement or the incumbent, they’re all running unopposed. This is an intolerable situation, IMO.
Allowing any Republican, all (save for Justin Amash) of whom have shown themselves to be hapless sycophants, bowing to the whims of the most destructive and inhumane President in modern history, to run without any Democratic opposition is something we should avoid at all costs.
- Bill Cassidy, Louisiana (In 2014 he beat three-term incumbent, Democrat Mary Landrieu, 56 percent to 44 percent. Don’t know if there are any Democrats in the running at present.)
- Mike Enzi, Wyoming (Retiring – This seat is considered safe by most people.)
- Cindy Hyde-Smith, Mississippi (Hyde-Smith defeated Mike Espy last November in a racially charged campaign.)
- James Inhofe, Oklahoma (This is the schmuck who brought a snowball into the Senate chambers to make the argument that global warming can’t be possible because it’s still cold somewhere.)
- Pat Roberts, Kansas (Retiring – Maybe a lost cause, as he ran unopposed last time and Kansas is a deep red state)
- Mike Rounds, South Dakota (The entire state has approximately a quarter of a million voters. Unknown if there are enough Democrats to matter.)
- Ben Sasse, Nebraska (In the 2014 election, there were a little over a half million voters; Sasse won every county in the State – 64% to 31%)
- Dan Sullivan, Alaska (In the 2014 election, Sullivan won by 2.2% with a total of only a little over a quarter million voters. This state could be ripe for a flip.)
After the 2016 General Election, I worked with a group of people who were creating a canvassing tool that was designed to use AI to better prepare people who were out knocking on doors. It would have used demographics and historical voting data to train a machine learning algorithm on the patterns to be found in the data. Unfortunately, our primary investor kept adding requirements and ultimately squeezed the value right out of the app.
Nevertheless, our original concept we had discussed was to use machine learning to help political organizations make the most effective (not merely efficient) use of their various resources, e.g. time, money, people, connections, as well as understanding the political environment based on polls and overall news coverage.
Frankly, nobody I know of has sat down and begun to develop such a decision model, though I would dearly love to see it happen. It’s what we envisioned after Trump “won” and I still think it’s a viable approach. It does look like it’s a somewhat daunting challenge, however, when it comes to how expensive it would be to gather all the data we’d need access to, as well as develop the algorithms that would analyze and correlate the data.
Regardless, it seems a shame so many Republicans might run without any Democratic opposition. You’d think the least we can do is make them fight for their seats, which would include forcing them to shift resources around as well. It should be part of the overall pattern of the elections, which I’m unconvinced the Democratic Party really understands.