Uncertain Accountability In Medicine
- A diagnostic Artificial Intelligence company was faced with legal and diagnostic problems
- Firstly the same symptoms can have different meanings in different areas – in one area it may mean food poisoning, in another malaria
- If a diagnosis was incorrect, who was to blame – the company, the algorithm, the individual programmer or the doctor?
Brain Everywhere Solution
- Doctors trained models directly for each diagnosis in each area.
- As Brain Everywhere is 100% transparent and each outcome can be traced back to the original medical decision.
- It was clear that the doctor was the legal decision taker and that it fell under his/her malpractice insurance.
- Varied metrics depending on area and diagnosis – Brain Everywhere supported a suite of different models which could be easily modified per area
Success and Improvements
- The twin problems of diversity and accountability were eradicated
- The doctor’s insurers were willing to cover the Sue decisions as well
- Approx 1 doctor week per diagnosis
More Use Cases
Sue can convert any telemetry from a reactive rule base to a predictive model that will avoid unplanned stoppages and nip problems before they become critical. Sue is the ideal AI for IOT. With the vast amounts of telemetry being generated by IOT, there are not enough experts and engineers to read it all. Sue can read every telemetry reading and email / autocall / refertohuman when action is needed. IOT, Mining, High Precision Farming, Telcoms, Vehicle Monitoring
Sue can approve renewal of risks and bills risks within fuzzy thresholds. Underwriting, Utility Bills
Sue can predict missing data points in a set using the other data.
In any transactional environment, Sue can read every single transaction and flag outliers and exceptions for human review including fraud, money laundering or pricing. Sue is able to imitate an expert that reads a page of transactions and spots the fraudulent one. Except that Sue can read ALL the transactions in a large organization and never needs sleep. Telecoms, Banking, Finance, Triage of Insurance Claims
Call Centres Next Best Move
Sue can recommend the next best move based on what is put in on each screen, standardizing service and optimizing flows.
Sue can learn any individual decision in the medical field and replicate it
Sue is being used to analyse specific metrics, economic indicators, weighted risk parameters and soft input to take shareholding decisions ending in Buy/Hold/Sell. Transaction Pricing, Shares, Currency Trading, BlockChain Smart Contracts, Actutarial Pricing Methodology, Fitment of Statistical curves, Reserve Forecasting
Sue can act as a help desk able to run set scripts 24/7 anywhere in the world, detect data breaches and protect database by running scripts and smart approving every db/os action
You don’t need Cambridge Analytica to target advertisements or profile clients. With a few pieces of information Sue can segment your whole population and send each person the right message. Investment, Retail Deals, Politics
Most AI engines need 80 pieces of information to fire, leading to client fatigue. Sue can give an initial approval after as few as 3 parameters. Credit cards, Employee applications
Unlike humans, Sue can review every single item offered and give an initial unbiased opinion Underwriting, Risk Selection, Recruitment Selection, Holiday Authorizations, Exploration Predictions
Sue can read the psychometric results of a candidate and give you the probability of success in a division based on the results and performance assessments of other candidates.