1. Why did some previous attempts to use artificial intelli­gence technologies fail? What key differences of the new AI-based applications versus the old cause the authors to declare that automated decision making is finally coming of age? One reason that previous attempt to use artificial intelligence failed was because it was difficult to extract knowledge from the experts. It was also very expensive to keep running,so this definitely played a role in the demise of previous attempts. Due to limited capabilities there was a lack of business applications. There was also a lack of interest in the technology all together. Some of the key differences were the reduction of overhead, which primarily was due to maintenance. The new AI also was embeded directly into the workflow and was not a separate step in the process. The new one also translates into action.
2. What types of decisions are best suited for automated decision making? Provide several examples of successful applications from the companies in this case to illustrate your answer. There are many decisions best suited for automated decision making, but the first that stands out to me is that inputs are available electronically rather than human input. There is also more frequency in automated decision making. The automated decision making problems are not so broad, but are more narrow and well defined. One example of successful application is bank credit customers can complete the application within five minutes, at which point the automated process begins. After being used initially by airlines to optimize seat pricing, decision-making technology has since been applied to a variety of areas, includ­ing flight scheduling and crew and airport staff scheduling this is another good example of a successful application. Scheduling, staffing and fraud detection are some other good examples to illistrate sucessful applications. A credit report is pulled, the credit is scored, a property valu­ation is completed using online data, confirmations are made concerning fraud and flood insurance, and a final de­cision is made on the loan. 3. What role do humans play in automated decision-making applications? What are some of the challenges faced by managers where automated decision-making systems are being used? What solutions are needed to meet such challenges? Humans have the knowledge of engineering and they can think on their own. Humans also can make the decision to review something if something arises. Humans can also make the determination if they need to override a system. One challenge faced by managers is system input so that humans do not have to do it. Users would like fast and immediate services rendered and AI can provide the information as long as it has the correct data available. Another challenge is keeping the rule base up to date. This does not happen automatically, so the computer will give out of date solutions. One solution is that Managers can integrate internal systems as well as external data suppliers. Integration also supports CRM, data dash boards and digital warehousing too. Managers should keep up with all new knowledge bases, so that they are aware and vigilent in this ever changing IT field.