11.6 Visions of the future

that could be conveniently tailored to the patient group at hand. In all cases, the closed loop model can be employed, where the biosensor is the speech signal; hence, an indirect biosignal (see Figure 1.1). The (bio)feedback actuator can consist of (a combination of) a variety of elements among which are therapy session, physical or mental exercises, and the use of medicine. Further, please note that such CAD can also be brought closer to home. A PC could execute the models as presented in Chapter 8 without any problem, even in real time.

11.6 Visions of the future

The previous section discussed applications for which the knowledge and techniques needed are (near to) available. This section stretches way beyond that and looks into two possible future applications of ASP. These two applications touch upon various branches of computer science. Moreover, their possible implications will also force us to consider the ethical aspects of ASP.

11.6.1 Robot nannies

It was 2010, just one year ago, Sharkey and Sharkey [600] stated: “. . . robot manufacturers in South Korea and Japan are racing to fulfil that dream with affordable robot “nannies”. . . . By extrapolating from ongoing developments in other areas of robotics, we can get a reasonable idea of the facilities that childcare robots could have available to them over the next 5 to 15 years. ” [600, p. 161]. If this estimate is (near to) correct, robot nannies could already take care of my future grandchildren or even my children. This emphasizes that this vision of the future is near, very near, within one generation from now! Will this vision truly be our future or will it remain science fiction (for a while longer)?

Crucial in the development of children is infant attachment; that is “the deep emotional connection that an infant forms with his or her primary caregiver, often the mother.” [600, p. 174]. For children’s development, a good attachment is crucial. As Sharkey and Sharkey [600, p. 174] also state, “Responding appropriately to an infant’s cues requires a sensitive and subtle understanding of the infant’s needs.” This is also known as maternal sensitivity [166]. The seminal work of Harlow and colleagues [258–260] on baby monkeys already showed the importance of attachment for baby’s. Moreover, it enabled the identification of problems that emerge with insecure attachment. To establish maternal sensitivity a tailored emotional connection is required. Par excellence, robot nannies emphasize the need for AI to adopt models of human emotions, as has already been stressed many times throughout this monograph (in particular, see Chapter 1).

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11 Discussion

The case of robot nannies shows strong resemblances with AI’s Intelligent Tutoring Systems (ITS) [12, 621], a branch of expert systems that was vivid 25 years ago. ITS used models of children (i.e., the students aimed to use the ITS) extensively. However, these were tailored towards a specific (sub)domain, whereas robot nannies would need (more) generic models. This is precisely what ITS failed to deliver. Moreover, much more than with ITS, robot nannies should connect emotionally with the children they care for. ASP could facilitate such a connection, as has been shown throughout this monograph. However, this adds even more to the complexity of robot nannies, as ASP would need to be employed in the noisy real world; in particular, see Chapters 2 and 10 for a discussion on this. Moreover, this gives rise to the ethical aspects of future technology such as robot nannies and AmI [13].

Given the possibly wide implication of ASP-augmented technology such as robot nannies and AmI on our daily lives, ethical issues require a significant amount of attention, not after but before theory has become practice [200, 280, 525]. Regrettably, it has to be concluded that the resources that are provided for ethical considerations are scarce. Luckily, progress of science and engineering on emerging technology such as robot nannies, AmI, and ASP takes considerable time (cf. [89], [195], and [609]). Perhaps, this provides ethics the time to catch up. However, considering humanity’s history, I am afraid the chance that ethics will take a position in the forefront of science’s landscape is futile.

11.6.2 Digital Human Model

Throughout this monograph it has been noted repeatedly that, if anything, ASP needs a holistic approach. However, this has been noted before in other areas of application, amongst which biometrics. In this section, I will link ASP and biometrics to each other (cf. [326, 726]) with the aim to work towards a Digital Human Model (DHM). However, before touching upon this aim, I will provide a brief introduction to biometrics.

Four decades ago, IBM envisioned the identification of persons (ID) by machines [149]. IBM stated that this could be achieved through: i) something the user knows or memorizes, ii) something the user carries, and/or iii) a personal physical characteristic. From this concept, the field of biometrics emerged; that is, “. . . the science of establishing the identity of an individual based on the physical, chemical or behavioral attributes of the person.” [309, p. 1]. Essentially, biometrics is a signal processing + pattern recognition problem [309], just like ASP; see Chapter 1. It can be applied to either verify or identify an ID, which can be defined as:

where Ix is the representation (e.g., a vector) of an unidentified person, his bioprofile. In is

Biometrics is derived from the Greek language and means: life measuring.

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the nTH sample from the database (DB). D is a distance metric (e.g., a Minkowsky or quadratic metric) [507] and T is a threshold. Note that in the case Eq. 11.1 results in Ix = Ix, the person remains unidentified after the DB is consulted. In case of verification of persons, 1 : 1 matching is applied. So, the DB, as depicted in Eq. 11.1, contains one profile. Then, maxn{D(Ix, In)} < T becomes D(Ix, In) < T . In practice, frequently a way in between 1 : 1 and 1 : n matching is employed. The bioprofiles that are matched can be built based on:

1.Behavioral attributes; for example, signature, keystroke dynamics, and gait;

2.Physical attributes: fingerprint, iris and retina, facial image and facial thermogram, geometrical features of the face; for example, ear and nose [459] and geometrical features of the hand and feet [175];

3.Other: audio-based (e.g., voice), chemical attributes (e.g., odor), and DNA,

which can be classified using a taxonomy on biometrics [309]. As is illustrated by this enumeration, bioprofiles share various signals with ASP; for example ECG [300, 345] and EEG [436]. Hence, not surprisingly, biometric taxonomy shares dimensions with ASP (cf. Chaper 10), namely: obtrusiveness, user acceptance, overt versus covert, validity (e.g., the reliability and discriminative power compared with the other signals applied).

ASP can reveal psychological aspects of a person alongside to physiological aspects and as such become a new class of biometrics. From multi-modal (traditional) biometrics, a range of behavioral, chemical, and physical characteristics can be derived. Together ASP and biometrics can lay the foundation for a digital human model (DHM; cf. [172, Chapters 16 and 35] and e.g., [726]). On the one hand, a DHM can be seen as the ultimate model for biometrics. On the other hand, a DHM satisfies ASP’s need for a holistic approach. The development of a DHM is a vision that will not be easily met.

Building DHM is a process in which law and ethics will claim their place too (cf. [13, 200, 280, 525]). Law considerations comprise: i) rules of privacy, ii) the constitutional background, and iii) privacy under law, including physical, decisional, and information privacy [309, Ch. 18]. People cannot prevent personal information (e.g., biosignals) from being collected by various actors. Therefore, “several security measures are implemented on servers to minimize the possibility of a privacy violation. Unfortunately, even the most well defended servers are subject to attacks and, however much one trusts a hosting organism/company, such trust does not last forever.” [11]. One of the possible solutions would be a “degradation model, where sensitive data undergoes a progressive and irreversible degradation from an accurate state at collection time, to intermediate but still informative fuzzy states, to complete disappearance. We introduce the data degradation model and identify related technical challenges and open issues.” [11]. More even than with traditional biometrics, DHM requires an adequate handling of this issue.

Ethical considerations emerge from the notion that DHM would enable a much broader information collection than solely a person’s (rational) ID. One of the ethical issues

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