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Manager, Indian Library on AI & Law
Apr 08, 2021
In Law of the Seas
Introduction: The Global Maritime Distress & Safety System (GMDSS). Abstract The objective is to study & understand the aforementioned piece of innovation, its scope; & its limitations. Methodology A doctrinal methodology has been followed. Subject Matter The GMDSS is an internationally recognized distress and radio communication safety system for ships replacing the previous ship to ship safety system, which relied on a manual Morse code system on 500 kHz and voice radiotelephony on Channel 16 and 2182 kHz. The GMDSS is an automated ship to shore system using satellites and digital selective calling technology.[1] The GMDSS establishes the radiocommunications equipment that ships are required to carry, how this equipment shall be maintained and how it is used, and provides the context within which governments should establish the appropriate shore-based facilities to support GMDSS communications.[2] Analysis The GMDSS is mandated for ships internationally by the International Maritime Organization (IMO) Safety of Life at Sea Convention (SOLAS), 1974, as amended in 1988, and carries the force of an international treaty. The procedures governing use are contained in the International Telecommunication Union recommendations and in the International Radio Regulations, and also carry the force of an International Treaty. All ships over 300 gross tonnage on international voyages are subject to the SOLAS convention and must comply with the carriage requirements of the GMDSS. The equipment carriage requirements will be determined by the area in which a vessel is operating within otherwise known as sea areas. The GMDSS therefore includes a provision whereby each government that chooses to sign the SOLAS Convention (called a Contracting Government) “… undertakes to make available, as it deems practical and necessary either individually or in co-operation with other Contracting Governments, appropriate shore-based facilities for space and terrestrial communications …”. This undertaking establishes one of the really significant features of the GMDSS infrastructure: some communication systems will use facilities that are essentially international in nature and not under the control or supervision of any single government. It is this that gives rise directly to the need for the international community to establish special arrangements for the international supervision of satellite-based communication facilities for the GMDSS, which have been developed and are implemented by International Mobile Satellite Organization (IMSO). All of the data included within the GMDSS system is part of the MSI data which as suggested by the IMSO is coupled with intelligent receivers can discriminate between information that is relevant to a particular ship and other information that is not, automatically discarding those messages that are not relevant to the ship in which the particular receiver is carried.[3] However serving of such MSI data through servers like NAVTEX and SafetyNet are again essential treaty obligations of the states and have to be followed. GMDSS Consists of INMARSAT – a global mobile satellite communication system providing two-way data and messaging. NAVTEX - an international automated service for delivery of navigational and meteorological warnings, forecasts and urgent maritime safety information to ships. Emergency position indicator radio beacon (EPIRB) – automated identification and locator device for Search and Rescue operations. Search and Rescue locating equipment – automatically leading Search and Rescue units to the position of distress by signaling search and rescue radar transponders. Digital selective calling (DSC) - a standard for sending pre-defined digital messages from ship to ship, ship to shore and shore to ship. DSC is considered the automated watch on distress channels running on VHF, MF/HF radios. The satellite communication is based on satellite network that reaches up to sea area A3. Emergency Position Indicating Radio beacon’s (EPIRB) and Search and Research transponders (SART) are sending out distress and locating signals under emergencies. EPIRB’s are small portable devices using the global COSPAS-SARSAT Satellite System and sending signals on the 406MHz frequency, whereas the SART devices are portable radar transponders operating on the radar ”X” and ”S” frequency bands. The Search and Rescue transponders can stay afloat, when a ship has sunk and are also used on life boats. EPIRB automatically send distress signals, when coming in contact with water. [4] While, the application of AI can be seen in most of the GDMSS system due to their satellite communication feature, it is preferable to discuss about DSC due to its automation features. DSC-equipped VHF radios can send an automated distress signal over VHF radio frequencies with one push of a button, allowing even an inexperienced user to signal for help. Once this button is pushed, the radio will continue to send the distress signal, complete with the vessel’s unique nine-digit identifier, even if the captain and crew are disabled. Digital selective calling-equipped radios also can hail a specific vessel privately , provided it’s also equipped with a marine DCS VHF radio. According to industry group BoatUS, this means boats don’t have to monitor high-traffic channels to listen for hails; instead, the radio will signal a call with a ring and then switch automatically to the calling channel.[5] The DSC is a synchronous system using characters composed from a ten-bit error detecting code. The bits are encoded using frequency shift keying. For High Frequency and Medium Frequency two tones 170 Hz apart either side of the allocated frequency with 100 Baud symbol rate are used. For VHF the two tones used are 1300 and 2100 Hz with a symbol rate of 1200 Baud. Each character is transmitted twice with a time delay. The detailed specification is published in the International Telecommunications Union recommendation ITU-R M.493, revision 15 being the most recent.[6] Conclusion Therefore, even though one can argue that DSC is not a mandatory treaty obligation but one of the main aims of the SOLAS Convention was safety and protection of ships on the high seas and GMDSS is an integral part of it as is AIS collision avoidance system both of which cannot be discarded. Therefore, GMDSS and DSC in specific serve as an example wherein AI or automation technology has entered the legal regime through one of the highest form of legal obligations, i.e., treaty obligations. However, in this case it is not only IMO, but also the obligations under ITU and IMSO that are to be followed. Nevertheless it has to be specified herein that all of these obligations originate from the comity obligations and the obligation to maintain the safety of international maritime navigation and transport under the International Maritime Origination which many countries have also imbibed in their national legislative structure.[7] Name of the Author: Sayan Chandra. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00009 Style: Typical; Most Similar; [1] https://www.fcc.gov/bureau-divisions/mobility-division/ship-radio-stations/global-maritime-distress-and-safety-system [2] https://imso.org/gmdss/ [3] Ibid. [4] https://www.danphone.com/coastal-radio-navtex-ais/gmdss/ [5] https://gizmostimes.com/marine-dsc-vhf-radio-what-is-digital-selective-calling/ [6] "M.493 : Digital selective-calling system for use in the maritime mobile service". International telecommunications Union. 2019. [7] https://www.amsa.gov.au/safety-navigation/navigation-systems/global-maritime-distress-and-safety-system-handbook-2018; https://www.fcc.gov/bureau-divisions/mobility-division/ship-radio-stations/global-maritime-distress-and-safety-system
Global Maritime Distress & Safety System content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Law of the Seas
Introduction: The Maritime Single Widow - a legally introduced electronic business solution by the IMO under the SOLAS Convention for the integration of communication services. Abstract The aim is to understand the concept of 'Maritime Single Window' as an innovation & The threats it brings & The usages it has. Methodology A doctrinal approach has been taken towards the fulfillment of the above aims. Subject Matter The Maritime Single Widow is a legally introduced electronic business solution by the IMO under the SOLAS Convention for the integration of communication services. It can enable all the information required by public authorities in connection with the arrival, stay and departure of ships, persons and cargo, to be submitted via a single portal without duplication. Recommended Practice 1.3quin in the FAL Convention encourages the use of the "single window" concept. The conceptual model of MSW consists of an environment whereby ship data providers can submit information electronically either through a user interface or a system-to-system interface. The information is digitized, and the individual data elements will be submitted once only.[1] The IMO also suggests that an automated information transaction system may in some cases simplify the overall design of the complete system by allowing legacy document formats to be used. Analysis The mandatory requirement for national governments to introduce electronic information exchange between ships and ports came into effect from 8 April 2019, under the FAL Convention. According to the Standard 1.3bis, Public Authorities have to establish systems for the electronic exchange of information by 8 April 2019. A period of no less than 12 months for transition to the mandatory use of the systems shall be provided from the date of the introduction of such systems. In addition, Recommended Practice 1.3quin encourages the use of the "single window" concept, to enable all the information required by public authorities in connection with the arrival, stay and departure of ships, persons and cargo, to be submitted via a single portal without duplication. The obligation to create systems for the electronic interchange of information established by Standard 1.3bis does not refer specifically to "single window", so the Contracting Governments can use system other than it to comply with this obligation too. In fact, the single window concept is propagated by the IMO for integration and standardization of practices with regard to electronic business. This is the reason why the IMO Guidelines with regard to a Maritime Single Window which was introduced in April 2019 specify that they do not define any particular standard for implementing a single window. They point to different internationally recognized standards that are available and that can be utilized as appropriate.[2] Further, the amended FAL Convention mandates the use of modern information and communication technology and, in particular, electronic exchange of information, including electronic data interchange (EDI), to transmit information related to maritime transport. The use of EDI is a central part of the conceptual architecture.[3] The FAL Convention and the FAL Compendium define the maximum amount of clearance information that may be required before a ship can go to berth that has to be inducted through the MSW. The FAL Compendium identifies data format standards that can be used to implement system collaboration of an MSW and promote interoperability. Another important aspect of interoperability is ensuring legally significant trusted trans-boundary electronic interaction of documents between stakeholders from different jurisdictions.[4] Shipping companies engaged in international trade regularly have to submit large volumes of information and documents to ports and governmental authorities, in order to comply with regulatory requirements. The information often has to be submitted through several different agencies, each with its own specific system and paper forms. These requirements, together with the associated compliance costs, constitute a burden both to Governments and to the business community and can be a major barrier to the development of international trade, particularly in developing countries. Establishing a Single Window facility is one means of addressing this problem. It can enhance the availability and handling of information, and can simplify and expedite information flows between trade and government. It can also bring about greater harmonization and better sharing of the relevant data across governmental systems, bringing meaningful gains to all parties involved in cross-border trade. The interchange can take place using UN/EDIFACT, XML or any other standardized file format. It is important however that all formats comply with international standards, particularly where trade has a preference for one or more standards, as this reduces the cost of compliance for trade for exchanging information.[5] UNECE is the abbreviation for the United Nations Economic Commission for Europe. UN/EDIFACT is the abbreviation for the United Nations Electronic Data Interchange for Administration, Commerce and Transport. It is a special format defined by UN/CEFACT and later standardized by the International Organization for Standardization (ISO) as the ISO 9735 standards.[6] Besides the MSW, there are also Port Community Systems, Port Single Window, Trade Single Window, etc. A PCS is defined by IPCSA(International Port Community Systems Association) as a neutral and open electronic platform enabling intelligent and secure exchange of information between public and private stakeholders in order to improve the competitive position of the sea and air portsʹ communities; and optimizes, manages and automates port and logistics processes through a single submission of data and connecting transport and logistics chains.[7] In light of the dramatic increase in the use of digitalized systems across the maritime sector, the FAL Committee has considered the facilitation aspects of protecting the maritime transport network from cyber threats, including the need to address particular risks to maritime single windows, processes for electronic certificates and data exchange between ships and shore, pre-arrival information based on the Facilitation Convention and processes involving ship-port interface. The management of cyber risk should be done in accordance with international standards and best practices including the Guidelines on maritime cyber risk management (MSC-FAL.1/Circ.3), which provides high-level recommendations for maritime cyber risk management. Conclusion Therefore, the MSW Concept is a concept which has attained the level of treaty obligation wherein in accordance to the international maritime trade policy it is required to follow an electronic centralized approach for the exchange of trade related information for various national compliance. Even automation to that extent is allowed by IMO. Herein not only observance of comity obligations but also aligning national standards and policy requirements with the international requirements becomes a concern especially where the FAL Convention requires that only a maximum limit of prescribed data only can be sought for maritime clearance. The integration of electronic technology in such an environment is a perfect example of conjugation between AI and international maritime law. Name of the Author: Sayan Chandra. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00008 Style: Typical; Most Similar; [1] https://wwwcdn.imo.org/localresources/en/OurWork/Facilitation/Documents/FAL.5-Circ.42.pdf at p. 5.2 [2] https://wwwcdn.imo.org/localresources/en/OurWork/Facilitation/Documents/FAL.5-Circ.42.pdf (FAL.5/Circ.42) at p. 2.4. [3] Ibid. at p. 5.2 [4] https://wwwcdn.imo.org/localresources/en/OurWork/Facilitation/Documents/FAL.5-Circ.42.pdf at p. 7 [5] https://wwwcdn.imo.org/localresources/en/OurWork/Facilitation/Documents/FAL.5-Circ.42.pdf at p. 3.3.1 [6] Ibid. at p. 3.3.2. [7] Ibid. at p. 3.4.5
Maritime Single Window content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Law of the Seas
Introduction: Long-range identification and tracking system provides for the global identification and tracking of ships. This system is tracked and maintained by the International Maritime Organization. Abstract The International LRIT Data Centre (IDC) is an element of the LRIT system that receives, stores and disseminates LRIT information on behalf of Contracting Governments to the 1974 SOLAS Convention. In the context of the LRIT system architecture, technical specifications International LRIT Data Centre addresses the functional specifications for the IDC.[1] The purpose of the study is the- understanding of the aforementioned innovation; The legal implications thereof; & the aspect of its amalgamation with artificial intelligence. Methodology A doctrinal methodology has been followed to achieve the aforementioned aims. Subject Matter The obligations of ships to transmit LRIT information and the rights and obligations of SOLAS Contracting Governments and of Search and rescue services to receive LRIT information are established in regulation V/19-1 of the 1974 SOLAS Convention. The amendments to the International Convention for The Safety of Life at Sea, 1974 introduced in 2006 which provides the international law basis for use of the LRIT Data Exchange Platform. However, the Regulation 19.1 provides that no regulation for LRIT should prejudice the rights, jurisdiction or obligations of States under international law, in particular, the legal regimes of the high seas, the exclusive economic zone, the contiguous zone, the territorial seas or the straits used for international navigation and archipelagic sea lanes.[2] There are multiple legal protections under this rider that are available to contracting states. Firstly the equipment used for sending the LRIT should be able to be switched off or cease the distribution of information, where international agreements, rules or standards provide for the protection of navigational information; or in exceptional circumstances and for the shortest duration possible where the operation is considered by the master to compromise the safety or security of the ship. [3] In exchange for the sharing of LRIT information all contracting states are also entitled to receive such LRIT data from other contracting states with ships which are entitled to fly their flags.[4] Besides, even the functional and technical requirements for the equipment to be used for the sending of the LRIT data is to set by the contracting states in accordance to their national regulations and laws. The LRIT system consists of the shipborne LRIT information transmitting equipment, the Communication Service Provider(s), the Application Service Provider(s), the LRIT Data Centre(s), including any related Vessel Monitoring System(s), the LRIT Data Distribution Plan and the International LRIT Data Exchange. Certain aspects of the performance of the LRIT system are reviewed or audited by the LRIT Coordinator acting on behalf of all SOLAS Contracting Governments. Analysis Tracking of any applicable ship begins with LRIT information being transmitted from the shipborne equipment. The LRIT information transmitted includes the ship's GNSS position (based on the WGS 84 datum), time and identification. The Communication Service Provider (CSP) provides the communication infrastructure and services that are necessary for establishing a communication path between the ship and the Application Service Provider (ASP). The LRIT information transmitted from the ship travels across the communication path set up by the CSP to the ASP. The ASP, after receiving the LRIT information from the ship, adds additional information to the LRIT message and passes the expanded message to its associated DC. Functionality required for the programming and communicating of commands to the shipborne equipment is provided by the ASP. DCs disseminate LRIT information to LRIT Data Users according to the LRIT Data Distribution Plan (DDP). The DDP contains the information required by the DCs for determining how LRIT information is distributed to the various Contracting Governments. The DDP contains information such as standing orders from Contracting Governments and geographical polygons relating to Contracting Governments' coastal waters. LRIT Data Users might be entitled to receive or request LRIT information in their capacity as a flag State, port State, coastal State or Search and Rescue (SAR) service.[5] The International LRIT Data Exchange (IDE) is a message handling service that facilitates the exchange of LRIT information amongst DCs to enable LRIT Data Users to obtain that LRIT information that they are entitled to receive. The IDE routes messages between DCs. Implementation of the IDE, for example, could consist of a high-speed computer running IDE specific application software. The IDE application software could consist of various software modules such as a DC interface module, message processing module, billing module, Quality of Service (QoS) monitoring module, etc.[6] The LRIT system also includes handling of message specifications, storage specifications, communication specifications, encoding specifications carried out by the DCs on various software applications which are again worked under the guidance of the LRIT Coordinator which works under the authority of IMO. All the data is entered into the Testing and Production environments of the LRIT Data Distribution Plan (DDP) the information provided by each Contracting Government. Then the related LRIT identities will be created by the Secretariat and the Contracting Government concerned will be considered as having met the requirements of paragraphs 11.2.1 (in part); 11.2.5 to 11.2.8; 11.2.10 and 11.2.11 of the Revised performance standards. Further, information on ports within the territory or jurisdiction of a Contracting Government should be communicated to the Organization in an XML format to facilitate the electronic processing and importing of the information into GISIS.[7] Therefore the LRIT functions as a huge data exchange center controlled by software applications which also has simultaneous observance of the international law obligations existing. Conclusion The LRIT provides the perfect example of conjugation of international maritime law and AI whereby the IMO has laid down in depth specifications of each technical standard required for the LRIT. Because the formation of the LRIT is a treaty obligation and cannot be contracted out of but more so because it works on comity obligations and in order to ensure the safe and equitable navigation of the high seas, hampering of which can lead to serious international law issues like the Corfu Channel Case between UK and Albania. Name of Author: Sayan Chandra. Date of Publication: 08 April, 2021 Indicative Code: ILAIL-0000-CS-08-04-2921-00007 Style: Typical; Most Similar; Deviant; [1] https://wwwcdn.imo.org/localresources/en/OurWork/Safety/Documents/LRIT/1259-Rev.8.pdf at p. 1.1.2.5 [2] International Convention for The Safety of Life at Sea, 1974, Regulation 19.1 (Introduced by MSC 81/25/Add.1) https://wwwcdn.imo.org/localresources/en/OurWork/Safety/Documents/LRIT/MSC.202(81).pdf [3] Ibid. at Regulation 19.1.7 [4] Ibid. at Regulation 19.1.8.2 [5] https://wwwcdn.imo.org/localresources/en/OurWork/Safety/Documents/LRIT/1259-Rev.8.pdf at p. 1.2.2.4- 1.2.2.7 [6] Ibid. at p. 1.3.3.1 [7] https://wwwcdn.imo.org/localresources/en/OurWork/Safety/Documents/LRIT/INF-16.pdf at p. 3.1 to 3.7
LRIT (Long Range Identification & Tracking) content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Transportation Law
Introduction: Implementation of AI in the Railway Infrastructure(s). Abstract The objective is to understand the implications of AI in transport via railway. Further concern being the prevention of accidents & mechanical failures. Relevant references to mechanisms have been made to gain a grasp on the practical aspects. Methodology A doctrinal approach is taken to achieve the aforementioned objectives. Subject Matter Artificial intelligence (AI) is having a profound effect on our personal and professional lives alike, including across the transportation sector. In particular, powerful new AI-enabled applications are helping boost and revive the global rail industry, which has suffered for decades due to lack of innovation. Railway sector is not any different from such innovation. This has led to Railways being again looked in a favourable manner due to its environmental friendliness, efficiency, and cost-competitiveness relative to other modes of transport. ARC Advisory Group expects to see the digitalization of the railways happening at a rapid pace. However, for railways to reap the full benefits of digitalization, it must expand its use of AI across both rail operations and rail infrastructure.[1] A.I has been in transportation sector for past 50 years however it has come to a wide use in railways in pass few years and in the transportation sector as a whole it has made all transport modes safer, cleaner, smarter, and more reliable. AI can help reduce traffic congestion, identify risks, manage transport, analyze travel demands, and even reduce greenhouse gas emissions. Today, we’re seeing AI being used in rail applications to improve train scheduling, manage train speeds, avoid accidents, predict delays, enhance asset management, and more. These AI applications help ensure public safety, deliver customer value, and optimize overall rail management and operations. In this manner, the technology is helping reverse the trend for rail transport to lose market share to other modes of transportation.[2] Artificial Intelligence is being applied to improve efficiencies and reduce costs across a variety of train control system, safety, supervision, and asset management systems, one of the effective examples of uses of AI in rail technology is its contribution to the automation of train operation (ATO).[1] ATO is a technology used in train which is used to transfers responsibility of managing operations from the driver of train to the Artificial intelligence to control the trainsystem, these system has varying degrees of autonomy which is similar to different autonomy in artificial intelligence driven car.[2] Analysis The International Electrotechnical Commission has established four standard grades of train automation: First one is where the artificial intelligence in train only advises the driver about any defect or detachment of rails[3] The second one is where the Artificial intelligence is used to close the door of the train and has all the features of first one.[4] The third grade corresponds to driverless operations (with crew members present on board)[3] and The fourth grade to autonomous and unattended train operations. These examples are already visible in light rail and urban transit systems.[5] The Dubai International Airport operates a fully autonomous train to transfer passengers from one terminal to another in a defined track system. It uses SelTrac, an automatic railway signaling technology to control the train autonomously.[6] The Singapore Mass Rapid Transit Lines, currently the world’s longest automated metro system, is another example. This urban transit system is at fourth-grade automation. In the EU, the first key step towards the introduction of ATO and AI solutions in rail transport is the deployment of the European Rail Traffic Management System (ERTMS), which provides trains with a driver assistance system.[7] In India also the Artificial intelligence in provided for railways by a company called Gaia which provides A real-time Onboard Housekeeping Service (OBHS) management that not only manages people onboard but also manages operation processes. The system collects data via IoT sensors as well as users’ devices in real-time, with time and location stamps to ensure data efficacy and accountability of the entire working in Indian Railways. The IoT devices are paired with sensors to enable last-mile monitoring of parameters such as temperature, pressure, humidity, power usage, faults, proximity, footfall, and other metrics to understand site and asset performance in real-time.[8] It then uses AI algorithms for allocation, optimisation, and task orchestration. A comprehensive action and workflow engine complement the platform for managing alerts and incidents, triggering workflows, and enabling closed-loop response management. The solution is a multi-tenanted platform that allows role-based access for users – from line staff and managers to senior management and board-level executives – on a unified platform.[9] These kinds of technology are most use in the Tejas express which runs in India.[10] Similar kind of technology was being to be used in Delhi metro to make it driverless however due to an human error the Delhi metro crashed in the wall just after the a station.[11] Conclusion From the above incidence it is clear that though Artificial intelligence is being used to make our work easy however there are still a lot of improvement that has to happen such as to easily distinguish between a human and an unidentical item so as to prevent what has happened in the uber driver case where a car thought women was unidentified object and ran over her and taking away her life secondly there should be a training program to make sure that the user of the transport knows how to operate a vehicle so as to prevent the accident that happened with Boeing 737 Max and lastly there should be awareness among humans to prevent the king of accident that happened with Delhi metro if these things are taken into account then Artificial Intelligence would be one of the most useful thing which can make our life much more easier than it is today however it would take almost a decade or two to reach that perfection level. Name of Author: Ansh Kumar. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00006 Style: Typical; Influential; Most Similar; [1] Artificial Intelligence in Rail, WASAY RASHID, ARC Advisory Group, ( Mar. 26, 2021, 22:40) https://www.arcweb.com/blog/artificial-intelligence-rail#:~:text=AI%20can%20help%20reduce%20traffic,enhance%20asset%20management%2C%20and%20more. [2] Supra at 36 [3] Supra at 36 [4] Supra at 36 [5] Supra at 36 [6] Supra at 36 [7] Supra at 30 [8] How Indian Railways Uses AI: A Comprehensive Case Study, Sejuti Das, Analytics India mag, (Mar. 26, 2021, 23:07) https://analyticsindiamag.com/how-indian-railways-uses-ai-a-comprehensive-case-study/ [9] Ibid [10] Supra at 46 [11] Delhi Metro's Driverless Magenta Line Train Crashes Days Before Launch By PM Modi, Mukesh Singh Sengar, NDTV India, (Mar. 26, 2021, 23:12) https://www.ndtv.com/india-news/delhi-metros-magenta-line-crashes-into-wall-during-test-run-1789709
AI vis-a-vis Railway content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Transportation Law
Introduction: Hypothetical Accident of an Autonomous UBER cab. Abstract The purpose is the understanding of autonomy per se in terms of auto-driven vehicles. Furthermore, through an hypothetical instance cited, an analysis of how far the negligence of a human entity availing the said vehicle can be deemed as punishable is made. Methodology A doctrinal approach is taken to achieve the aforementioned objectives. Subject Matter The self-driven car is powered by Artificial intelligence. To create such car the developers uses vast amount of data to create a real time image that is saved in created in the car that helps is car to be driven without the help of human[1] it can be explained through example Google's self-driving car project, called Waymo, uses a mix of sensors, Lidar (light detection and ranging -- a technology similar to radar) and cameras and combines all of the data those systems generate to identify everything around the vehicle and predict what those objects might do next.[2] The car functions as follows:- The driver (or passenger) sets a destination. The car's software calculates a route.[3] A rotating, roof-mounted Lidar sensor monitors a 60-meter range around the car and creates a dynamic three-dimensional (3D) map of the car's current environment.[4] A sensor on the left rear wheel monitors sideways movement to detect the car's position relative to the 3D map.[5] Radar systems in the front and rear bumpers calculate distances to obstacles. AI software in the car is connected to all the sensors and collects input from Google Street View and video cameras inside the car.[6] The AI simulates human perceptual and decision-making processes using deep learning and controls actions in driver control systems, such as steering and brakes. The car's software consults Google Maps for advance notice of things like landmarks, traffic signs and lights.[7] An override function is available to enable a human to take control of the vehicle.[8] Also it provides with 5 level of automation they are as follows: - Level 1: - It includes an advanced driver assistance this aid and advises the human driver with when to accelerate and when to apply break and it also has a rear view camera and a vibrating seat which would vibrate and give the warning to driver when they travel out of the traveling lane.[9] Level 2: - It has advanced driver assistance which can steer and either do break or accelerate while the driver is still in control of the car.[10] Level 3: - Here the advanced driver assistance can drive the car under certain circumstances such as doing parking. However the human driver should be in full awareness to take the control of car if the car goes out of control due to A.I fault.[11] Level 4: - An advanced driver assistance can perform all driving function in certain circumstances and human should not pay attention while car do all the function.[12] Level 5: - In this the advanced driver assistance acts as a virtual chauffeur and does all the driving in all circumstances. The human occupants are passengers and are never expected to drive the vehicle.[13] Further there is sensor installed in the car which helps in sensing the other cars in surroundings this is an addition security to camera so that if one security fails then another would act and helps the car to drive.[14] Analysis In this hypothetical scenario, an uber self-driven car having level 2/3 automation, whose owner left the car on auto drive mode and the car misidentified a women as an unidentified object and crashed into the said woman and killed her. Later investigation revealed that the car didn’t have "the capability to classify an object as a pedestrian unless that object was near a crosswalk,"[1] Because the car couldn't recognize Herzberg as a pedestrian or a person — instead alternating between classifications of "vehicle, bicycle, and other" — it couldn't correctly predict her path and concluded that it needed to brake just 1.3 seconds before it struck her as she wheeled her bicycle across the street a little before 10 p.m.[2] However, when the Police investigated the matter further it was held that it was the fault of the human as he could have taken the control of the car as it was not fully automated and he could have taken control easily and the person was consequently sentenced to imprisonment.[3] In this case the owner of the car had an opportunity to take on the control of the car but he didn’t, causing the conduct to be come negligent and the owner is thus liable as held in case of Palsgraf v Long Island Railroad Co.[4] that - if person a didn’t act in a duly diligent manner and was negligent, then he is liable to pay compensation. So in this case as well, the person should be made liable and asked to pay compensation to the family of deceased and also on the basis of the principle of master servant relation, uber company can be made liable and uber can take compensation from the driver.[5] Conclusion It can be safely concluded that - based upon the technology standards & benchmarks prevalent today, the arising of such a situation as mentioned above would be cause for consequential results as mentioned above respectively with minor variations only in facts but not point(s) of law or precedents, except if proper frameworks are designed. Name of the Author: Ansh Kumar. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00005 Style: Typical; Influential; Most Similar; [1] Self-driving Uber car that hit and killed woman did not recognize that pedestrians jaywalk, Phil McCausland, NBC NEWS, ( Mar. 25, 2021, 23:46) https://www.nbcnews.com/tech/tech-news/self-driving-uber-car-hit-killed-woman-did-not-recognize-n1079281 [2] Uber's self-driving operator charged over fatal crash, RoRy – Cellan Jones, B.B.C. News U.K ( Mar. 25, 2021, 23:48) https://www.bbc.com/news/technology-54175359 [3] Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam, The New York Times, ( Mar. 25, 2021, 23:53) https://www.nytimes.com/2018/03/19/technology/uber-driverless-fatality.html [4] Palsgraf v Long Island Railroad Co [1928] 248 NY 339 [5] Vicarious Liability in case of Master-Servant Relationship in Tort Law, Monika, Ipleaders, (Mar 26, 2021, 00:07) https://blog.ipleaders.in/vicarious-liability-case-master-servant-relationship-tort-law/#:~:text=In%20a%20Master%2DServant%20relationship,master%20is%20also%20held%20liable. [1] self-driving car (autonomous car or driverless car), Ben Lutkevich, TechTarget Network, (Mar. 25, 2021, 23:05), https://searchenterpriseai.techtarget.com/definition/driverless-car#:~:text=AI%20software%20in%20the%20car,such%20as%20steering%20and%20brakes. [2] Ibid [3] Supra at 17 [4] Supra at 17 [5] Supra at 17 [6] Supra at 17 [7] Supra at 17 [8] Supra at 17 [9] How AI Is Paving the Way for Autonomous Cars, Rilind Elezaj, Machine Design, (Mar. 25, 2021, 23:22) https://www.machinedesign.com/mechanical-motion-systems/article/21838234/how-ai-is-paving-the-way-for-autonomous-cars [10] Ibid [11] Supra at 25 [12] Supra at 25 [13] Supra at 17 [14] Artificial intelligence in transport Current and future developments, opportunities and challenges, European Parliament, (Mar. 25, 2021, 23:36) https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/635609/EPRS_BRI(2019)635609_EN.pdf
Hypothetical Autonomous UBER Accident content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Civil Aviation Law
Introduction: Case Study of the Crash of one Ethiopian Airline Boeing 737 Max owing to Mechanical Failure of AI based Mechanism. Abstract The objective is to understand how crucial an AI mechanism can be in terms of areas such as Civil Aviation. A relevant study is done, which demonstrates beyond reasonable doubt how important keeping up to date with new technology is. The study as well provides how nascent we are in terms of AI technology & how rapidly developing the field is. The study also shows how much personnel need to be aware & trained. Methodology A doctrinal approach is taken to achieve the aforementioned objectives. Subject Matter Before we go into details of what happened in this particular case, how Artificial Intelligence works in Airline industries needs to be explained. When the crash happened the airline was using the Boeing 737 Max which has a Maneuvering Characteristics Augmentation System (MCAS) which is a flight control law implemented on the 737 MAX to improve aircraft handling characteristics and decrease pitch-up tendency at elevated angles of attack.[1] MCAS (Maneuvering Characteristics Augmentation System) is implemented on the 737 MAX to enhance longitudinal stability characteristics with flaps up and at elevated Angles of Attack (AoA).[2] The MCAS function commands nose down stabilizer to enhance pitch characteristics during steep turns with elevated load factors and during flaps up flight at airspeeds approaching stall. MCAS is activated without pilot input and only operates in manual, flaps up flight.[3] The system is designed to allow the flight crew to use column trim switch or stabilizer aisle stand cutout switches to override MCAS input this was bought after 2 crashes of Boeing 737 Max crashed.[4] The function is commanded by the Flight Control Computer (FCC) using input data from sensors and other airplane systems. The MCAS function becomes active when the AoA exceeds a threshold based on airspeed and altitude. After AoA falls below the hysteresis threshold (0.5 degrees below the activation angle), MCAS commands nose up stabilizer to return the aircraft to the trim state that existed before the MCAS activation.[5] This system are generally placed near the engine where there are sensors to detect if the angle of attack is more than needed and which would cause the plane to stall, these new types of engines are called The LEAP-1B engine using which the Boeing wanted to make a comeback to aviation industry[6] These system were bought by the boeing to prevent stall from happening. A stall is when the tilt of planes is so great that a plane can no longer increase it’s height and it is bound to fall.[7] Analysis Now coming back to the case of accident of Ethopian Airlines, in this case a Boeing 737 Max was being flown which took off from Ethiopian capital Addis Ababa at 08:38 local time (05:38 GMT) on 10 March for a two-hour flight to the Kenyan capital, Nairobi. Six minutes later, at 08:44, it crashed 30 miles southeast of the airport, near the town of Bishoftu. The impact was so great, both engines were buried at a depth of 10m (32ft), in a crater 28m wide and 40m long. The preliminary report into the accident, by Ethiopia's Aircraft Accident Investigation Bureau, said the plane's take-off appeared normal. However, a short time later two sensors that measured the angle of the plane's flight began to record different readings[8] This happened because the sensors which were installed in these aircrafts gave false readings which caused the Maneuvering Characteristics Augmentation System to be activated and push down the nose of the aircraft which led to the plane going into landing mode. The pilots of the plane tried to pull up the plane but the system is made in such a way that it would override any human input.[9] This is similar to the Lion Air Flight 610 which also crashed immediately after take off. These two were similar as the graphs which were recorded showed that in both the cases the pilots of the planes tried to pull up the nose of the plane but the Maneuvering Characteristics Augmentation system falsely detected that the Angle of Attack is greater than normal and it would stall the plane and it caused both the planes to crash despite pilot action the system overrode its input and crashed.[10] After this incident all the Boeing 737 Max aircrafts were grounded all over the world due to the safety issue and a notice was issued to Boeing[11] about how to turn off the Maneuvering Characteristics Augmentation system, it said that there is a red button on the flight control which has to be pressed then CPU should turned off and then RPM then should be adjusted manually.[12] After this notice an improvement was bought by Boeing Maneuvering Characteristics Augmentation system, in this the MCAS software had been modified and now uses two AoA sensors, not one. The MCAS also now only activates once, rather than multiple times, when a potential stall is signaled by both the AoA sensors. Pilots are provided with an “AoA disagree warning” which indicates that there might be an erroneous activation of MCAS. This warning was not standard equipment at the time of the two accidents – it had to be purchased by airlines as an option.[13] Further the pilots will now be trained in the operation of the MCAS and management of its problems however the pilots were not trained or even told that Maneuvering Characteristics Augmentation system existed[14] So These actions have improved the quality of the airplane and increase its security and we can hope that there would no more such kind of accident of Boeing aircrafts in future due to failure of A.I. Conclusion It's of the utmost importance that no expense be spared by body corporates regarding keeping up with emerging technology for the sake of not only their businesses but the sake of the personnel they employ as well. Research & Development along with Spreading of Awareness & Training needs to be taken into consideration at each & every juncture of integrating new technology & each time newer technologies that can have wider implications on the field/ industry in question come about. Name of Author: Ansh Kumar. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00004 Style of Case Study: Typical; Most Similar; [1] Maneuvering Characteristics Augmentation System (MCAS), sky brary, ( Mar. 25, 2021, 19:36) https://www.skybrary.aero/index.php/Maneuvering_Characteristics_Augmentation_System_(MCAS)#:~:text=MCAS%2C%20or%20Maneuvering%20Characteristics%20Augmentation,at%20elevated%20angles%20of%20attack [2] Ibid [3] Supra at 2 [4] Supra at 1 [5] Supra at 2 [6] 737 Max updates, The latest Information, updates and statement on the 737 Max, Boeing, (Mar. 25, 2021, 19:47) https://www.boeing.com/commercial/737max/737-max-software-updates.page [7] Supra at 2 [8] Supra at 1 [9] 6 Minutes of Terror: What Passengers and Crew Experienced Aboard Ethiopian Airlines Flight 302, Jeff Wise, New York Intelligencer, (Mar. 25, 2021, 20:14) https://nymag.com/intelligencer/2019/04/what-passengers-experienced-on-the-ethiopian-airlines-flight.html [10] Ibid [11] Boeing 737 Max: why was it grounded, what has been fixed and is it enough?, the conversation, ( Mar. 25, 2021, 20:38) https://theconversation.com/boeing-737-max-why-was-it-grounded-what-has-been-fixed-and-is-it-enough-150688 [12] Supra at 1 [13] Supra at 12 [14] Supra at 12
Accident of Ethiopean Airline's Boeing 737 MAX.  content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Economic & Trade Law
Introduction: Case Study on Responsible AI implementation with Higher than Expected Employee Retention. Abstract The study is aimed towards understanding how implementation of AI mechanisms can be done, while bearing in mind that employees should be retained in the best way & best numbers possible. Such an instance is cited, & analyzed, to understand the implications that the said maneuver can have. Methodology A Doctrinal Approach has been taken. Analysis Tata Steel Europe has aimed to digitise its production basing this on key factors like the need to improve profit margin in already low profit margin industry that already over produces and supplies compared to the demand, the demand for more quality products and the aging workforce. It kept a focus on its employees and decided to retrain its employees to better understand the technical aspects of its recent development. They utilized data visualization tools in order to aid the explainability and interpretability of the Advanced Analytics models[1]. Concerning its productivity, it saw a 13 % increase in EBITDA (Earnings Before Interest, Tax, Depreciation and Amortization) with the same workforce. It was also noted that the Advance Analytics program broke even within one or two years of its implementation in regards to the capital investment and offered a higher return on investment later. The benefits were seen in the form of raw materials savings, yield improvements and margin improvements.[2] It was seen that in some areas the profitability was much larger especially in cases of raw materials as they were the largest cost driver in the Tata Steel Europe’s cost analysis. It was seen that there was no major workforce reduction in the operations of TSE though in the long run it is noted that there will be a workforce reduction but it is expected to be within the norms of the industry standards. TSE has tried to utilize the existing workforce and does not aim to completely overhaul the same with Artificial Intelligence. It aims to look for savings in terms of raw materials savings, yield improvements and margin improvements. The lack of workforce reduction in TSE’s operations may be attributable to a string workforce union. However, that does not mean that TSE’s workforce remains unchanged, it is seen that there is an increasing trend of higher trained workers in its composition thus there were higher trained workers than lower trained ones, this may also be in part to the focus placed upon retraining the pre-existing workforce. This way Tata Steel Europe aims to set an example of a corporate leader. It also recently implemented Digitate’s cognitive automation solution ignio as its AI platform for IT operations.[3] It aims to transform their IT operations providing better services while focusing on the machinery.[4] It is clear from the case study of Tata Steel Europe that AI systems is an analytical tool and the adoption of AI can be done tactfully and in a much better manner. It is also seen that it is much easier for highly profitable firms to adopt Artificial Intelligence systems as it is a capital-intensive undertaking which can increase global income inequality.[5] Conclusion A solemn conclusion can be drawn that the fears of the global citizenry with regards to AI & recession are ill founded, & must be done away with. On the part of body corporates, an understanding needs to be present as to the requirements of the employees & the global citizenry with regards to employment. The TSE instance shows that not only can retention be positive in terms of humanistic values but can as well serve to bring in incremented revenues. Name of Author: Nalin Malhotra. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00003 Style of Case Study: Influential; Deviant; Diverse; [1] https://www.partnershiponai.org/case-study/tata-steel-europe-in-brief/ [2] Id. [3] https://digitate.com/newsroom/ignio-powers-it-transformation-at-tata-steel-europe/ [4] Id. [5] Autor DH et al, 2017b. The fall of the labor share and the rise of superstar firms, NBER Working Paper No. 23396 (Cambridge, MA, National Bureau of Economic Research).
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Space Law
Introduction: Brief Analyses of the methods & implementations of ISRO & SpaceX in terms of AI in space. Abstract The study aims at understanding of certain limitations faced by us as humans with placing & utilization of AI in terms of Space exploration, research &/or other such projects & the laws concerned therein. Methodology A doctrinal methodology is adhered to. Subject Matter AI has wide ranging applications in space industry and is often utilised for a variety of purposes such as space debris monitoring, making automated decisions like that of the Mars rover, weather surveillance etc. It has been frequently used in space as it is a service-based industry. Currently AI is used in space activities in two ways - 1. Autonomous Space Objects: These are autonomous bodies, robots, satellite construction and etc. that not only analyses data but also conduct activities that would not be possible for humans such as collecting data, probes, preserving space assets, Active Debris Removal (ADR) 2. Analysis of the data collected such as conducting a predictive analysis from very high satellite imagery, geospatial analysis, debris monitoring, these large datasets can also be stored via space cloud computing i.e., where data is stored on space-based assets. The primary concerns when it comes to AI in space are privacy issues such as citizen tracking, fake imagery, biased automatic decision making etc. And liability issues such as damages caused by autonomous spacecrafts for e.g., collisions, malware etc. These concerns have been exacerbated and the confidentiality of the information that has been given is now on the minds of the people. Artificial Intelligence based technologies are able to handle a lot of structured and unstructured datasets and are able to derive information out of them[1], that may have been missed by a human and prone to human errors, the possibility of missing critical and relevant information has necessitated the use of technology-based solutions that ease this derivation of information[2]. Sensors from outer space collect massive spatial data[3], the storage and analytical costs of which are very high and it would be really difficult to analyze the same without any help. Analyses Case Study of ISRO ISRO has not been behind the world in utilizing AI based technology for its missions. Chandrayaan II delivered Pragyan a solar powered vehicle that would explore the lunar surface, it consisted of LIBS (Laser Induced Breakdown Spectroscope) to identify elements present near the landing site and APIXS (Alpha Particle Induced X-ray Spectroscope) to inspect the composition of the elements identified by LIBS near the landing site. The rover could communicate with the lander utilizing motion technology to help maneuver the rover and complete its landing. It also comprised AI algorithms that could identify the mineral and determine its composition. The rover by the help of Artificial Intelligence could also determine any faint traces of water on the lunar surface. Through the Artificial Intelligence system, the rover could send the pictures of the lunar surface back to ISRO where they could be analyzed and used for research. It has also developed a humanoid robot called Vyom-mitra literally translated to Space Friend. In order to conduct long duration crew flight while decreasing human risks and errors. The robot would utilize Artificial Intelligence tools to carry out various procedures like operate heavy machinery and facial recognition. Though initially it is expected to carry out solo missions the aim is to make it suitable as a fellow crewmate a bit similar to C3P0 or TARS from interstellar. The robot would also contain various sensors such as gravitational de-acceleration, heat noise etc. that would be used to make long duration space flight as comfortable for humans as possible. These features would be crucial to support life on Environment Control and Life Support Systems like Gaganyaan where the robot is expected to support the crew members.[4] In its recent report on Research Areas in Space it has also outlined its aim to develop vyomnoids that would support the crew members and help in the mission by way of Artificial Intelligence algorithms.[5] ISRO has also designed and developed National Remote Sensing Centre to detect deforestation and combat it. It detects small scale changes in forest covers to detect deforestation and increase the frequency of reporting such changes, it has utilized this remote sensing technology to increase the time it would take to analyze such changes and their subsequent reporting from a year to one month. It has also developed Image Processing and Pattern Recognition (IIRS) by way of Artificial Neural Networks and deep learning programs in cases of earth observation.[6] Case Study of SpaceX SpaceX has gained a lot of prominence in the commercial sector for its space missions and in its mission, Dragon is piloted by a sophisticated Artificial Intelligence system that guides the rocket to the International Space Station.[7] This mission also included the first of a kind robot in space called SIMON who can use facial recognition and orient itself and hover over to the geophysicist Gerst.[8] It has been described as a flying brain. Though it has a limited programming as of now, it can converse and provide technical support but not much as of now. Its aim is to assist the crew members in performing scientific experiments that are needed to be carried out. It has been described to be similar to an Alexa for space.[9] It has also started to use AI systems to avoid collisions out in space. In its Starlink launch where it launched 60 satellites where most of them would be in the Lower Earth Orbit that has been filled with space debris, When SpaceX would receive a possible conjunction alert they would send the information to the satellites that would conduct evasive maneuvers by way of its electric thrusters thus avoiding collision with any possible space debris. Conclusion It's indeed wonderful how the concepts of 'Vyom-mitra' & 'Vyomanoids' have been conceded, & it shall be yet more wonderful to be able to experience the exhibition of the facilities & opportunities such innovations shall open up the doors to for India. ISROs focus upon not only major concerns such as space exploration but a concern on the Earth & the environment proves how much India cares about its flora & shall prove to undoubtedly be a great endeavor. Space Debris Detection would as well undoubtedly prove to be an incredible endeavor, minimizing the risk to human life for astronauts. The foci on robotic life-forms with purposes of assisting space exploration & life in space is very well though of, & highly innovative. However, it's of the utmost importance that the legal implications ranging from privacy to autonomy be considered. So that no infringements can occur & policies/regulations can be effectively framed. Name of Author: Nalin Malhotra. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00002 Style of Case Study: Diverse; Influential; [1] Goodwin, S.: Data rich, information poor (drip) syndrome: is there a treatment? Radiology management 18(3) (1996) 45–49. [2] https://towardsdatascience.com/artificial-intelligence-for-internal-audit-and-risk-management-94e509129d49#2402 [3] P. Soille, S. Loekken, and S. Albani (Eds.) Proc. of the 2019 conference on Big Data from Space (BIDS 2019), EUR 29660 EN, Publications Office of the European Union,Luxembourg 2019 https://www.bigdatafromspace2019.org/QuickEventWebsitePortal/2019-conference-on-big-data-from-space-bids19/bids-2019 [4] https://www.financialexpress.com/lifestyle/science/isro-gaganyaan-vyomamitra-vyomnauts-lady-robot-space-mission/1832947/ [5] https://www.isro.gov.in/sites/default/files/article-files/research-and-academia-interface/supported-areas-of-research/research_areas_in_space.pdf [6] https://developer-shubham-rasal.medium.com/how-isro-uses-machine-learning-25be23430713 [7] https://www.dexlabanalytics.com/blog/how-ai-powers-space-missions-like-those-of-spacexs-a-study [8] https://www.firstpost.com/tech/science/ai-robot-flying-brain-blasts-off-towards-iss-aboard-spacex-spacecraft-4643821.html [9] https://www.washingtonpost.com/news/the-switch/wp/2018/06/29/spacex-is-flying-an-artificially-intelligent-robot-named-cimon-to-the-international-space-station/
ISRO & SpaceX content media
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Manager, Indian Library on AI & Law
Apr 08, 2021
In Intl. Law & Gaming
Introduction: Take Two Interactive's AI & Radiant AI - Innovations in the gaming sphere vis-a-vis AI. Abstract: From IBM’s Deep Blue AI system that eat Garry Kasparov to Bethesda’s Radiant AI that allows NPCs in games to make dynamic decisions and make choices that was majorly expanded in Skyrim to Rockstar’s Red Dead Redemption where NPCs react dynamically to the player character, AI in gaming has come a long way. The objectives of this study: Understanding of the dynamics present in the sphere. Acknowledging the innovation & importance prevalent. Methodology: A Doctrinal approach has been taken towards the understanding & compilation of the study. Analysis: Take Two interactive’s AI Only a few game nerds would know that Rockstar is a subsidiary of Take Two Interactive, in fact the company has various Rockstar subsidiaries with the recent one being Rockstar Dundee. Recently a patent was filed by the company outlining a better method for AI to create and give players a realistic environment such as via better pathfinding. It is noted in the gaming industry that in order to create realistic environments the specifically large scale outdoor environment that become very difficult as more and more NPCs are concerned, the recent CDPR’s game cyberpunk is an example of the same. This new patent titled “System And Method For Virtual Navigation In A Gaming Environment,” aims to create a more realistic simulation by offloading the majority of the work from a virtual network to the cloud, as the patent states[1] "the system comprising a server for managing the virtual navigation of the one or more non-player characters; and one or more player consoles in operable communication with the server over a network, each player console comprising a gaming platform for executing the gaming environment, wherein said server generates a coarse graph of the low-level nodes and associated links, and pathfinds on at least one of the low-level nodes and the coarse graph from a start node to a target node, wherein pathfinding on the coarse graph reduces the number of loads of low-level nodes needed by the one or more player consoles to generate a path from the start node to the target node” The images of the same patent are reproduced below[2]: In short what this patent aims to achieve is for NPCs to become a little bit more organic, Rockstar states that the convention AI solutions only allowed limited NPCs solutions and would become more taxing on the engine when more NPCs are added. They run on limited scripts that only allow a limited number of actions, most NPCs only drive at the same speed etc. As the company puts it, it aims to create an environment where some NPCs would have more organic and individual scripts for e.g., an NPC might intentionally take side roads to avoid traffic jams, etc.[3] Radiant AI Radiant AI is an AI system that was developed by Bethesda first introduced in its Elder Scrolls game franchise, specifically Oblivion and later expanded upon by its later more successful release Skyrim. It allows the NPCs to make their own choices, therefore now not only do NPCs run different scripts such as sleeping, eating, killing etc., they also have the ability to choose between these scripts. In case of Oblivion, these scripts were managed by an internal responsibility system called lawfulness, what this entailed that NPCs with lower lawfulness are more likely to commit acts such as murder, theft etc. therefore, NPCs like Bandits and Thieves would commit random murders and thefts across the world map.[4] However, this AI system was also toned down as it would end up creating scenarios that would hinder the game’s scripts and quests. For example, in the case of one quest where the player was supposed to meet a shady skooma (an in-game drug) dealer, the dealer would end up being killed as addicts would keep buying the skooma and when the inventory eventually ends, they would kill him. As a result, Bethesda deliberately toned down this AI system. In the case of Skyrim, the Radiant AI system was expanded by making the NPCs run unique scripts from different towns and cities and was also utilized as a Radiant Story system where in order to increase for example friendship with an NPC you would be given a radiant quest to go do something[5] for example a fetch quest for a sword for the mercenary Amren. Though this radiant AI system offered its own benefits it still does not tap into the true potential of the AI system, also NPCs could react to the player’s skills and say something accordingly such as a Guard might comment on the NPC having a really high stealth skill. Bethesda is also utilizing procedural generation for its next game called Starfield and as per Todd Howard, the game is set to have the biggest map in Bethesda’s history which is saying something as Bethesda has always had the penchant for making big world maps. As per Bethesda instead of opting for handcrafted world maps they are looking to utilize procedurally generated world maps in order to create maps faster. As we can see from the above two examples the most common utilization of AI in gaming is to make NPC scripts that would increase the player immersion[6] and pathfinding where the main problem is getting NPCs from one place to another amidst obstacles, different terrain etc.[7] As a result most academics do not consider gaming AI to be true AI unlike academic AI where the point is to provide analyses and help in decision making from large unstructured datasets game AI usually uses scripts and rule of thumbs to create an immersive experience. However, the use of academic AI for games have been seen but these games are usually very simplistic and non-scalable thus they don’t have viability in the commercial market.[8] Conclusion The most major factor holding back the potentially huge developments that AI can bring in the field(s) of gaming happens to be lesser viability of Game AIs in the commercial markets. It's of the utmost importance for techies & entrepreneurs & lawyers alike to understand the importance of games & the immersion that they might be able to create. Especially considering the amount of revenue that is generated by the gaming industry. NPC Intelligence & immersive worlds are what draws a gamer in, but the plot is what draws in hard-boiled campaigners. When an NPC makes a choice that affects the plot itself, that is the USP for the game. Name of Author: Nalin Malhotra. Date of Publication: 08 April, 2021. Indicative Code: ILAIL-0000-CS-08-04-2021-00001 Style of Case Study: Typical; Influential. [1] https://www.pcgamer.com/take-two-interactive-patent-could-point-to-a-bigger-better-world-for-the-next-grand-theft-auto/ [2] Id. [3] https://www.vg247.com/2021/01/18/gta-6-rockstar-patent-npc-ai/ [4] https://medium.com/the-unpublished/the-elder-scrolls-iv-oblivion-and-the-notorious-radiant-artificial-intelligence-4996636473b [5] https://www.gamesradar.com/remember-skyrims-radiant-ai-its-got-the-potential-to-revolutionise-rpgs/ [6] Good, Owen S. (5 August 2017). "Skyrim mod makes NPC interactions less scripted, more Sims-like". Polygon. Retrieved 16 April 2018. [7] Yannakakis, G. N. (2012, May). Game AI revisited. In Proceedings of the 9th conference on Computing Frontiers (pp. 285–292). ACM. [8] Yannakakis, Geogios N (2012). "Game AI revisited" (PDF). Proceedings of the 9th Conference on Computing Frontiers: 285–292. Archived (PDF) from the original on 8 August 2014.
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