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Date	November 2017	Marks available	12	Reference code	17N.1.HL.TZ0.5
Level	HL	Paper	1	Time zone	no time zone
Command term	Discuss	Question number	5	Adapted from	N/A

Question

Using a Segway with machine learning capabilities?

The Segway Patroller is a two-wheeled, battery-powered electric vehicle. Recently, Segway Patrollers have been used for security purposes in cities as well as in public spaces such as concerts, railway stations and shopping malls.

The Segway Patroller can travel up to a speed of 20 kilometres per hour (about 12 miles per hour) and travel about 40 kilometres (25 miles) in distance before the battery needs to be recharged.

Figure 3: A Segway Patroller

[Copyright: Urban Mobility GmbH – from https://en.wikipedia.org/wiki/File:Segway_Polizei_4.jpg]

Each Segway Patroller can be customized by adding the following features.

A global positioning system (GPS)-based navigation system
Machine learning capabilities that include speech, image and pattern recognition

The managers at Oliverstadt Station claim the introduction of upgraded Segways that have a GPS navigation system and machine learning capabilities would lead to improvements in the customer service provided.

Discuss whether the Segway Patrollers at Oliverstadt Station should be upgraded to include machine learning capabilities.

Markscheme

Answers may include:

Reasons for upgrading the Segway Patrollers to include machine learning capabilities (claim):

It will not require staff to have such a good knowledge of the geography of the train station and will reduce staff training costs (intuition, judgement, feasibility).
The routes selected by the Segway will be the most efficient ones.
Routes can be predetermined, and the route-finding algorithm can be programmed to avoid possible collisions / create a one-way system / accommodate peculiarities in the flow of passengers in the train station (systems, feasibility).
If a platform changes at very short notice the user only has to type in the new location and the route-finding algorithm will be able to adapt the route used (automation).
Management would be able to monitor the location of the staff because the Segway will be constantly communicating with the navigation centre and may make cost savings (values, ethics).

Reasons for not upgrading the Segway Patrollers to include machine learning capabilities (counter-claim):

If there is an accident involving a Segway, who would be accountable?
The constant upgrading of the software may not have been tested thoroughly, so the autonomous nature of the Segway may not be as effective as intended (reliability, feasibility).
The particular nature of Oliverstadt train station may mean that the algorithms used in route finding could conflict with the movement of passengers and may cause problems that can be avoided by having a human in control (acceptability).
The movement of passengers within the train station may not fit clearly defined patterns, so matching the patterns of passenger movements may be problematic and the algorithms may not provide the optimal solution (systems).
Train stations have to change the platforms that the trains leave at very short notice. Will the route-finding algorithm be able to respond immediately to these changes?
There may be considerable costs in terms of time and costs in determining the most appropriate algorithms, which are not compensated for by the reduction in staff costs / or efficiencies gained by autonomous Segways.
The human “pilots” of the Segway may have particular skills, such as linguistic abilities, that are not utilized when the dispatching of the Segway is more automated (systems).
The Segway may collect information about passenger movements that is not made known to them, a lack of transparency or possibly surveillance (values, ethics).

In this question it is expected there will be a balance between the terminology related to digital systems and the terminology related to social and ethical impacts.

Keywords: automation, connectivity, change, power, control, systems, values, ethics, machine learning, accountability, transparency, autonomy, surveillance, monitoring, algorithm, reliability, cost, feasibility

Refer to HL paper 1 Section B markbands when awarding marks. These can be found under the "Your tests" tab > supplemental materials > Digital society markbands and guidance document.