News & Insights
We’re Making History in Real Time.
Our timely insights share informed perspectives on the rapidly evolving story of Election Technology, as it unfolds.
Election Truths and Trustworthy Agents
In my last two posts, I wrote about the problem of falsehood-prone (a.k.a. lying) Chatbots giving out bad information on elections, and about dodgy chatbots that specifically refuse to say anything about elections and other specific hot topics. I answered some who/what/why questions and ended with the question of “What would be better?” This time, I offer a more complete answer...
Who Should Make an Elections AI Service Agent? (Part 6)
In this final installment of how to build an NLA (a domain-specific or DS-NLA) — the how informing the who question (that we started with back in mid-Dec ‘23) — I focus on what may be the most overlooked set of questions about how a system should be built — not just for serving users, but supporting it’s operators…
Who Should Make an Elections AI Service Agent? (Part 5)
In the previous (4th) installment in this series, we pivoted from the question of who can or should build Chatbots, to the challenge of How to build a safe, low-tolerance, domain-specific natural language agent (NLA or “DS-NLA”). This time, we assume for the moment that challenge is tractable and explore the question, “What else is required, in addition to a safe base model?”…
Who Should Make a Voter AI Chatbot? (Part 4)
After an extended holiday break from my last installment on the question: “Who should make a Chatbot for voters?” — I’m back for the 4th installment in this series. This time, I’m pivoting from the Who question to the How question; and I have definitely pivoted from “Chatbot” to “domain-specific natural language agent” (NLA)…