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#AI@Work: Are We Being Short Sited With AI?

The truth is that most of the programming and data analytics are created globally by white males. Research by CMU shows that women are less likely than men to be shown ads on Google for executive jobs. Correlations to unrecognized biases can be supple and it can be dangerous. From pay scales to types of observation and surveillance, these algorithmic flaws are not easy to detect. Ingrained bias could easily be passed on to machine-learning systems and be built into the future. Intelligent machines could learn to think in ways that mirror a male dominated, narrow, privileged society which supports familiar prejudices and stereotypes.

Far too often executives see only the short run. They don’t deal with the magnitude of overall change. This is because the scale and scope are too much to handle. Change in small and large organizations can be overwhelming. Leading agile transformations in the workplace is challenging. Trying to compete in a new marketplace with technologies so advanced will be an even more enormous challenge. Leadership needs to take ownership. These technologies offer new challenges and opportunities. No one is going to get it all right all the time. Learning and adjusting as the organization moves through change and grows will be paramount.

Changes in the workplace will start at the enterprise level. This will happen with a commitment to continuous improvement in products and services. The first step is to organize and commit to clear business objectives. Next, to form a team that will lead the workplace with continuous improvement processes. Employees need to understand the importance of change. This is a new and agile work environment. They need to be engaged in all aspects of the process. They also need support with learning and development opportunities

The majority of CEOs, about 71%, are sure that the next few years will be more important than the last fifty . Companies already use intelligent systems. This trend will continue to grow. Often there is difficulty in connecting new systemswith established systems. A greater awareness of the employees’ physical and cognitive activities can help when programming the systems. This is in the context of relevant tasks. Much work will need to be done to overcome the resistance to AI. Future workers will need the required AI skills. AI instills fear. This is usually of a plant or corporate closure. Employees will lose their jobs. In reality, it will be because of gross mismanagement. Workers fear massive job cuts and lack of retraining. Economics supports that labor is expensive and machines, once the original cost is overcome, are more competitive. Employees need to be involved in the development and process of change. They need to understand the implications of using new technologies and the future.

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