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Amstar Technologies successfully participated at IBM Developer Day 2019
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How an increased cost saving activity has helped Government stakeholders to find and allocate IBM Business Partners.

Recently the IBM Center for Business of Government and the Partnership for Public Service hosted a series of roundtables with government leaders to explore pressing issues surrounding AI, share best practices for addressing solvable challenges. This also involved creating a roadmap for government to maximize the benefits of AI. These discussions comprising tenets of business performance described the impact and potential performance improvements that AI will bring to government in areas such as effective workplaces, skilled workforces, and mission-focused secure programs.

IBM Partnership and the center also recently hosted a roundtable on February 5th 2019 which brought in panel experts for a discussion on how data, culture and technology will influence the policy decisions that government agencies need to make. This session was highly influential as it covered the potential of AI to help government identify AI challenges and how AI might impact the workforce to improve cost performance.

Below is a summary of the key findings addressed at the forum:
• Focusing on effective data management,
• Fostering a culture of innovation,
• Developing ethical AI policies, and
• Taking action to get started.
The roundtable explored avenues of how government can address bias and promote ethical imperatives in delivering effective adhoc AI solutions. Most importantly the areas of focus were
- Focusing on Effective Data Management
AI technology has solved complex problems in many high-tech private sector organizations. However, many government agencies cannot effectively utilize this technology because of poor data management practices. Legacy systems and processes continue to plague the agency’s ability to capture and analyze the full range of public sector data. Also outdated software tools are often incompatible with niche AI related programs thus making AI development difficult where we can definitely be of assistance to Government Bodies at Large wherein we also have offered unhindered support to the Government of Karnataka (GoK) at Large.

Furthermore, agencies still face challenges in sharing data thus limiting their capacity to benefit from AI. Agencies must cultivate a culture of data ownership and ensure that high quality data is available for AI systems decisions. Having processes in place for cleansing and appended data will avoid what some participants referred to as data “fratricide” wherein one data source eliminates the another and deletes valuable information present on server.

- Fostering a Culture of Innovation
In adopting AI, agencies face a combination of technical and cultural hurdles wherein cultural challenges can prove to be more difficult and address. While many agencies depend on a culture of experience based decision centric making, analysts on the other hand use their inbred domain knowledge and past expertise to arrive at a concrete solution.
Similarly, government agencies must also adopt a more agile approach to long and short problem solving. Success is defined by learning from experience in developing a viable product and as an emerging technology AI systems may periodically involve failure, bias or technical challenges where we can provide best adhoc technical consulting sessions.
Agency leaders have to create the space for producers and users of AI to fail and learn quickly from their mistakes. Addressing the inevitable technical challenges of AI systems will allow government to deploy these systems more successfully where we can definitely provide best the best assistance possible. Since many government employees believe that failure of any kind is unacceptable, leaders should emphasize that technical artifacts and outcomes represent only one measure of success where learning something new also brings value.
Change management will thus be a key element to building support for AI over time and focusing on learning will allow agencies to build communities of talented people that embrace a culture of innovation. Leaders should focus on empowering workers on the “front lines” to gain experience and domain knowledge and make the technology more accessible and equip their workforce across levels to leverage its full potential.

- Developing Ethical AI Policies

Private sector companies continue to be challenged to use AI ethically in order to retain public trust. Government use of AI involves far more than mere social media algorithms wherein AI can be used to pilot drones, audit taxes, or make decisions about security clearance status. Therefore, government agencies need to establish a firm guardrail around the use of AI technology more effectively.
Agencies need to critically assess ways that decision makers use in AI technologies to augment human decision making including assessing impact of a decision before and post applying automation. By doing this low-impact and repetitive tasks can be highly-automated, but high-impact tasks like clearance decisions which require greater human activity can be time-shared for higher work force optimization.
Algorithms used for high impact tasks should be transparent and explainable and explain how and why a decision was made which will also promote trust. Government agencies can further strengthen partnerships with industry and academic communities like the Institute of Electrical and Electronics Engineers (IEEE) and the Association for the Advancement of Artificial Intelligence (AAAI) to develop core principles of AI ethics. Such principles can apply widely to both technical and non-technical employees to effectively use them at workplaces.

- Taking Action to Get Started
In addition to creating ethical guidelines for AI-enabled tasks, agencies can begin implementing innovative technology in small ways which should be built early into the design of new AI systems. The first measure of success for AI systems should not be perfection, but whether the AI outperforms the older method and what can be learned from each iteration.
Agency leaders can get started on AI development by identifying champions with domain knowledge and enthusiasm for implementing AI to improve processes. Collaboration between leaders and front-line employees will help build momentum for AI adoption at ease.

- Conclusion
Implementing effective data management, fostering a culture of innovation, and establishing ethical policy guidelines all reflects important steps for agencies to take to utilize AI technology. Leaders should use these imperatives to take action, starting with small problems where AI can bring in significant value. By iterating on these solutions, agencies can learn on how best to understand and use AI consistently with a culture of innovation and progress where we can definitely assist corporates at large for their best IT outcomes.


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