AI Act

AI Act

Nepal should introduce national AI strategy. Nepal should work on policy-level intervention on Artificial Intelligence. Nepal should allocate substantial funding in research, training and skills in emerging technologies like AI. There is a need of forming an Inter-Ministerial National Artificial Intelligence Mission to act as a nodal agency for AI-related developments and activities in Nepal. Experts should be deployed by the government for creation of policy and legal framework for deployment of AI technologies, and provide recommendations for government, industry, and research programs. The lion ministry should focus on embedding AI for the country’s economic, political, and legal processes by leveraging key developments in industry domains such as manufacturing, fintech, healthcare, agriculture, education, retail, human and robot interaction, environment, national security, National Identity Card and public utility services.
The lion Ministry should frame a new Industrial Policy in consultation with all ministries, state governments, industries and stakeholders to align Nepal with latest technologies such as drones, AI, and blockchain. The policy has been outlined in sync with the challenges and opportunities in Nepal with Industry 4.0 technologies and to position Nepal in global supply and value chains. It will boost developments across areas like AI, blockchain, and analytics for innovation and business growth.

Developed countries are listing grand challenges for engineering in the 21st century, which includes things like securing cyberspace, advanced health informatics, personalized instruction and so on. Some countries are working on Algorithm Accountability Act which envisages that commercial enterprises would conduct assessments of high-risk systems that involve personal information or make automated decisions with the use of AI or machine learning. Some countries are ahead in implementing Privacy Rules and Bliley Act for the governance of data in the health and finance sector respectively. Stockbrokers, stock exchanges, Mutual Funds, Trustee companies are integrating AI and Machine Learning (ML).

The developed countries, like the UK, Canada, the UAE, Singapore, Japan, South Korea, and China have introduced their national AI strategy. They are working on prescribing for the ethics and minimum compliance mechanisms for AI ensuring that AI should be trustworthy, fair, cost effective, and free from bias and insecurities.


An aproach to AI Governance
As Nepalese youth aspires to develop its digital economy, a trusted ecosystem is key - one where organisations can benefit from tech innovations while consumers are confident to adopt and use AI. A serios awareness program shoud be launched by NGOS, INGOs and other grass root community service providers
In the global discourse on AI ethics and governance, countries believe that its balanced approach can facilitate innovation, safeguard consumer interests, and serve as a common global reference point.

An AI governance testing framework and a software toolkit are necessary The testing framework consists of 11 AI ethics principles* which jurisdictions around the world coalesce around, and are consistent with internationally recognised AI frameworks such as those from EU, OECD and AI Governance Framework. There should be a system, a single integrated software toolkit that operates within the user’s enterprise environment, should help help organisations validate the performance of their AI systems against these principles through standardised tests.
Such system should be able to perform technical tests on common supervised-learning classification and regression models for most tabular and image datasets.

The 11 governance principles are transparency, explainability, repeatability/reproducibility, safety, security, robustness, fairness, data governance, accountability, human agency and oversight, inclusive growth, societal and environmental well-being.


From Principles to Practice

Internal Governance Structures and Measures: Clear roles and responsibilities in your organisation
SOPs to monitor and manage risks Staff training
Determining the Level of Human Involvement in AI-Augmented Decision-Making : Appropriate degree of human involvement, Minimise the risk of harm to individuals
Operations Management: Minimise bias in data and model
Risk-based approach to measures such as explainability, robustness and regular tuning
Stakeholder Interaction and Communication: Make AI policies known to users, Allow users to provide feedback, if possible, Make communications easy to understand


Four areas of job redesign

Transforming Jobs: Assess the impact of AI on tasks, including whether each task can be automated or augmented by AI or remain in human hands, and decide which jobs can be transformed within an appropriate time frame.

Charting Clear Pathways Between Jobs: Chart task pathways between jobs within an organisation and identify the tasks employees would need to learn to transition from one job to another.

Clearing Barriers to Digital Transformation: Suggest ways to address potential challenges and support employees when implementing AI.

Enabling Effective Communication Between Employers and Employees: Enabling Effective Communication Between Employers and Employees

Guideline is required that will help organisations and employees understand how existing job roles can be redesigned to harness the potential of AI, so that the value of their work is increased. There should be practical approach to help companies manage AI's impact on employees, and for organisations that are adopting AI to prepare themselves for the digital future. THe approach should encourage organisations to take a human-centric approach to manage the impact of AI adoption by investing in redesigning jobs and reskilling employees. Trade associations and chambers, professional bodies, and interest groups use such documents for their discussions, and adapt it for their own use.

Nepal government should establish Advisory Council on the Ethical Use of AI & Data. This council should be
(a) advising the Government on ethical, policy and governance issues arising from the use of data-driven technologies in the private sector; and

(b) supporting the Government in providing general guidance to businesses to minimise ethical, governance and sustainability risks, and to mitigate adverse impact on consumers from the use of data-driven technologies.