AI-Governance – The Way Forward

Written By: Dr. Shahid Mahmud

The amount of data we produce doubles every year. In 2016, we produced as much data as in the entire history of humankind through 2015. Soon, the things around us, possibly even our clothing, also will be connected with the Internet. It is estimated that in 10 years’ time there will be 150 billion networked measuring sensors, 20 times more than people on earth. Then, the amount of data will double every 12 hours. Everything will become intelligent; soon we will not only have smart phones, but also smart homes, smart factories and smart cities. We should also expect these developments to result in smart nations and a smarter planet. Digitization of military assets, operations and processes is resulting in huge volumes of data being produced.

Why is This Critical?
To survive and thrive in the coming Artificial Intelligence (AI) enabled exponential-disruption, governments must proactively deal with the challenges and opportunities posed by AI. The field of artificial intelligence is making breathtaking advances. In particular, it is contributing to the automation of data analysis. Artificial intelligence is no longer programmed line by line, but is now capable of learning, thereby continuously developing itself. Recently, Google's Deep Mind algorithm taught itself how to win 49 Atari games. Algorithms can now recognize handwritten language and patterns almost as well as humans and even complete some tasks better than them. They are able to describe the contents of photos and videos. Today 70% of all financial transactions are performed by algorithms. News content is, in part, automatically generated. This all has radical economic consequences: in the coming 10 to 20 years around half of today's jobs will be replaced by algorithms. Because of the applications of AI, we are experiencing the greatest transformation since the end of the Second World War; after the automation of production and the creation of self-driving cars, the automation of society is next. With this, society is at the crossroads, which promises tremendous prospects but also considerable risks.

 

aigovernance.jpgModern defence organizations have been striving over the past two decades to achieve Network Centric Warfare (NCW) capabilities to address low intensity conflict, especially in urban environments, so that they can leverage information technology to turn information superiority into a competitive advantage. The information technology required to enable the superiority through NCW cannot be achieved by subsystems or individual systems, but need networked, cooperating and integrated system of systems (SoS). The integrated nature of the SoS, centered on an extensive communications network, facilitates the foundation for complete implementation of NCW.


Often in the past, these organizations pioneered both the development of technology and its application. Such is not the case today. Major advances in Information Technology are being driven primarily by the demands of the commercial sector and such organizations have led the evolution towards adopting a network-centric-approach-agility that has fueled business intelligence efficiently responding to market needs. These disruptive technologies that include big data analytics, artificial intelligence, internet and dedicated cloud infrastructures are defining how governance and operations of SoS is taking place.


Having a closer look at the core disruptors, it is becoming increasing fundamental to highlight the skill set required to adopt these technologies.


Data Deluge
The amount of data we produce doubles every year. In 2016, we produced as much data as in the entire history of humankind through 2015. Soon, the things around us, possibly even our clothing, also will be connected with the Internet. It is estimated that in 10 years’ time there will be 150 billion networked measuring sensors, 20 times more than people on earth. Then, the amount of data will double every 12 hours. Everything will become intelligent; soon we will not only have smart phones, but also smart homes, smart factories and smart cities. We should also expect these developments to result in smart nations and a smarter planet. Digitization of military assets, operations and processes is resulting in huge volumes of data being produced. Since 9/11, the amount of data from drones and other surveillance technology has risen 1,600 percent. The U.S. armed forces now have approximately 8 million computing devices – a number that is expected to double by 2020.


IoT Networks
The U.S. military has begun using the latest connected technology to assist soldiers and other military professionals in warfare. In particular, it’s placing a big emphasis on the data. The armed forces are collecting data from a range of different platforms, including aircraft, weapon systems, ground vehicles and troops in the field. Once this information has been created, it’s sent to intelligence, surveillance and reconnaissance systems. The latter are capable of pinpointing the most critical data for missions. The army is working with a few companies to help it integrate and use IoT solutions in daily operations. Lockheed Martin, for instance, is providing assistance on using machine learning to automate decision-making. This approach is helping the armed forces collect intelligence and identify key threats quicker and with more accuracy.


Advanced armed forces around the world are heading towards more integrated warfare approaches. The U.S. army has already implemented a classified IoT-based communication network line spanning 48,000 miles, which is being used in missile defence and battle coordination scenarios. This war fighting network merges elements of the army’s ballistic missile defence system into one central hub, which can be used to counteract threats all over the world. It takes data from hundreds of sensors, radars and satellites and translates that data into a common language for the missile defence systems to interact and engage the threat.


The AI Challenge
AI presents some alarming governance challenges. The most troubling perhaps has to do with the uncontrolled growth of deep AI or AGI in military robotics – at least 56 countries are currently developing battlefield robots. Gates, Musk, and Hawking are among those who have warned that proper governance must be placed around AI and military robotics integration or face the risk of military AI gone wild with potentially catastrophic consequences for humans. The fact that big data – and AI-centric functions – require exponential growth in data center facilities with significant capital and operational expenses. A significant risk involves computational ethics; an emerging discipline that seeks to provide machines not with “right” or “wrong” choices but with acceptable behavioral parameters within society.


What Should We be Asking Ourselves?
Government executives, military strategists, business community and the civil society have either ignored or taken AI for granted as outlook on these issues has been narrow without much consideration for their competitiveness and the impact on governance. As with other technological developments, the national leadership needs to understand the technical and socio-political landscape, evaluate the vulnerabilities, identify the value-based mechanisms, build national/organizational talent and demonstrate resilience to encourage an appropriate strategy and governance around this new element of national strength.

Capturing data, analyzing, acting and building possible future outcomes is the core function of big data analytics for the military, especially a force involved in counter-terrorism and public safety operations. However, it is of vital importance that the data collection, analytics and future forecasting functions be indigenously developed to safeguard against eavesdropping and intelligence gathering by foreign, non-allied entities. An indigenous data analytics and foresight laboratory is required to ensure independence and safeguarding against meddling from foreign influencers.

Therefore dimensions worth exploring in Pakistan’s context are:
How mature is the country’s use of big data analytics?
How pervasive is the country’s IoT deployment and analytics use?
How developed is the country’s fusion of various, previously disconnected data banks?
How proactive is the intelligence gathering and analysis of the country’s regional competitors, as well as non-traditional influencers using AI?


These three tenets should be closely observed regarding AI for effective governance:
The leadership is proactively engaged in AI strategy formulation, risk identification and oversight.
The leadership is proactively enabling expertise development and engagement of external experts to evaluate the intersection of AI with the defence’s core functions and services.
Functional and operational executives implement AI strategy collaboratively and in an integrated manner, through task forces or committees.


IoT Infrastructure
Designing, procurement and deployment of IoT infrastructure for various military-use-cases including smart metering, immersive virtual simulations for training, battlefield monitoring and awareness, unmanned systems, prevision targeting, flight-control systems, supply chain management, condition based maintenance, energy management, access control, threat detection, tactical communications, surveillance, crowd monitoring, fleet management, telemedicine, etc.


Indigenous Data Analytics and Scenario Building Futures Laboratory
Capturing data, analyzing, acting and building possible future outcomes is the core function of big data analytics for the military, especially a force involved in counter-terrorism and public safety operations. However, it is of vital importance that the data collection, analytics and future forecasting functions be indigenously developed to safeguard against eavesdropping and intelligence gathering by foreign, non-allied entities. An indigenous data analytics and foresight laboratory is required to ensure independence and safeguarding against meddling from foreign influencers.


Combat Cloud
Usually each branch of a defence force has its own infrastructure, both for connectivity and for the back-office systems. Transitioning to a combat cloud infrastructure would offer huge operational advantages, with greater ability to export both data and assets in the field for joint operations. When implemented, a combat cloud would allow information and control to move farther forward when appropriate, providing the operational flexibility to deal with a near peer targeting the national data systems.

 

The latest wave of technology governance focuses on thinking (artificially intelligent) machines that are not subservient to human input only – they can sense and make decisions on their own. AI and machine learning present unique complexities in governance that as a society we largely have not been forced to previously consider.

System Integrator
Defence sector does not inherently have the organic capacity to manage and oversee monumentally complex technology projects without diverting focus from its core functions. This is especially true in case of our regional security situation that is affected by continuous conflict, strategic national projects demanding stability, and a defence sector that is facing both internal and external covert and overt pressures. A responsible agent is needed to drive the technological evolution towards NCW (based on IoT, big data analytics and AI), manage risks across complex projects, ensure common vision, leading to a System of Systems that is greater than constituent parts. Modern defence forces, such as the U.S. military, have employed private contractors as Lead System Integrators (LSIs), to manage the development of selected SoS programs; because they accepted that the military did not have the organic managerial capability to oversee such monumental development tasks.


The New National Security Paradigm
AI is already disrupting traditional industries, e.g., the once ever-expanding Indian IT industry – addressing 15% of India’s annual exports at U.S. Dollars 100 billion – is now undergoing layoffs; cheap outsourced labor that performs routine tasks for North America (63%), the UK (13% ) and for other European countries (11%), is being eclipsed by the demand for artificial intelligence, cloud computing, big data analytics, robotic process automation, etc. These technologies require highly advanced skills, and to be competitive the Indian IT firms have to either replace or reskill their workers – both require an AI and big-data ready workforce. This is not only a regional but also a global problem, where there is less need for routine transactional employees.


The defence sector faces a similar challenge, where network centric warfare will depend on Systems of Systems, which will be coordinating and communicating in battlefield scenarios via AI and IoT enabled components. Managing these systems and remaining in control of the battlefield will require field commanders who are well versed with technology and military leaders adept at technology governance. Governments will have to bank on these skills as they too will be drawn to push for higher standards of cost and efficiency management against depleting resources. One innovative approach being utilised by DARPA’s Strategic Capabilities Office looks at how soldiers in battlefield will make strategic and tactical decisions when seemingly infinite informantion will be available to them through connected swarms of sensors; the challenge being to get soldiers as much information as possible, with as much learning applied to it in the simplest and clearest way. Pilot programs in which soldiers are being trained using machine learning based tactical augmented reality computer games are already underway.
Technology governance is not a new notion, we have already gone through various adoption phases of technology governance, starting from the advent of the steam engine, to the availability of wired communication and more recently with computing machines. However, the latest wave of technology governance focuses on thinking (artificially intelligent) machines that are not subservient to human input only – they can sense and make decisions on their own. AI and machine learning present unique complexities in governance that as a society we largely have not been forced to previously consider. Advanced countries are already making significant progress in this regard, with White House Office of Science and Technology Policy having set the foundation for domestic policymaking on issues related to machine intelligence, and the UK Parliament has also released a report on robotics and artificial intelligence policy. This is a new way of informing national security paradigm.

 

Dr. Shahid Mahmud, PhD in Artificial Intelligence is the CEO and Chairman of the Interactive Group of Companies. Has a Masters degree in Defence & Strategic Studies from National Defence University; and did his engineering from NED University. Dr. Mahmud is a Distinguished Eisenhower Fellow 2016

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