indicate that the problem might not be that the small print is too difficult for the participants to read, but rather that the participants revealed little intentions to read the small print and thus to change their behavior. Ultimately, it might seem paradoxical that the two women express concerns for their online privacy but are behaving contradictory as they exhibited little intentions to use privacy protective measures and thus change their behaviour.
Drawing on the research by Zeissig et al. (2017) there is found no privacy paradox to report in relation to older adults, as Zeissig et al. (2017) find a relation between those who had more privacy concerns also tend to exhibit more protective behaviours.
It should be noted that the study by Zeissig et al. (2017) uses intentions as its
operationalization measure. It would be interesting to have a study that measures participants’ actual
privacy behaviour and not merely their wish or intention to protect their privacy. This sort of study
might provide insight into what are the actual causal factors that individuals tend not to protect their
online privacy. Thus, if the older adults’ intention to protect themselves are high, as suggested by
Zeissig et al., (2017), but their actual privacy behaviour shows to be low, it might rather be a problem
of knowledge to protect themselves rather than the intention (Zeissig et al., 2017). However, this is
not possible to determine before the actual privacy behaviour of older adults has been covered in the
literature.
Participants’ associations with data (Sub-question 3)
Rather, the participants in both groups tended to express online privacy concerns in relation to data, which answers the research question in relation to: How participants associate online privacy concerns with data. The following four categories were topics the participants tended to associate with online privacy concerns: ‘Cross-domain tracking’, ‘small print’, ‘hacking’ and ‘giving up data in return for social benefits’. Common for all four topics are that they relate to the area of data and transparency (Cf. section 5.3).
In group one, online privacy concerns were associated with three main topics relating to data: ‘Cross-domain tracking’, ‘small print’ and ‘hacking’. These concerns for their data were expressed as a frustration that their data can be shared between different websites as they would not be able to know where there data would end up. Another frustration expressed was related to small print, which was perceived to be a problem as one needed to opt out of terms, instead of opting in.
Lastly, hacking was perceived to be a concern for the privacy of their data as strangers might be able to get in possession of their online data.
In group two, online privacy concerns were mainly associated with three topics relating to data: ‘Cross-domain tracking’, ‘small print’ and ‘giving up data in return for social benefits’. In general, some of the older adults found it concerning that, third parties were allowed to use their information that they had uploaded to e.g. Facebook and Instagram. Further, concerns related to small print was expressed, as small print was believed to be too long and the letters too small. Lastly, some of the older adults found it concerning that their data, in terms of pictures and text, could be used for targeting purposes, although, they seemed to find it challenging to be without the free social services, which they received from Messenger and Facebook. This indicated that the participants find it challenging to balance between the trade-off of social benefits versus the privacy harms that they endure.
Intentions to change online privacy behavior (Sub-question 4)
Several participants in both groups described how they found their online privacy to be infringed as they upload data online. However, neither the younger adults nor older adults exhibited any intentions to change their online behavior (Cf. section 5.4).
In the group with younger adults two possible reasons to this disparity emerged. First,
indolence seemed to influence the young adults. This was indicated as the their concern for online
privacy was not mirrored in their attitude as they indicated no intentions to change their behaviour
online. Secondly, it was also suggested by the findings in this paper that one reason that no privacy protective behaviour was exhibited could be due to a deliberated trade-off, in which the participant considers that information s/he is willing to give up in information in return for receiving social benefits online.
In the group with the older adults, there was a discussion among the participants about, whether, the reason that they do not read small print, was due to indolence, as argued by the male (CH), or due to the incomprehensible way that small print is presented, as argued by several women (HE)(GI). Judging from the participants’ comments, it appeared that the reason the participants were not reading the small print was due to indolence, as they seemed to give up trying to understand the services, since the participants did not exhibit any intentions to change their privacy online. Thus, these women also indicated a sense indolence.
The participants’ reasoning for their online privacy decisions in relation to the CPM theory
(Sub-question five)
It is concluded that the CPM theory has been able to provide a guiding framework in relation to which criteria are potentially influencing the participants as they create meanings and rules to help them decide whether to disclose information or not. However, the CMP theory has not proven sufficient to give a contemporary account of individuals’ online privacy decisions. Consequently, more recent studies have been included to examine each criteria in relation to privacy management.
In regard to the gendered criteria in CPM theory, the findings by Park (2015) helped to discuss why women in both groups reported more privacy concerns than the males (Cf. section 6.1.2).
Park’s (2015) findings indicate that privacy behavior differs by gender as he found that males have better technical skills and ability to protect themselves. And further, males have a broader confidence in regard to privacy protection than women. These findings might contribute to explaining pattern one (Cf. section 6.1.2.).
In regard to the Risk-Benefit ration criteria in CPM theory, the findings by De and Imine (2018 (b)) provide a model that can help the participants to better balance the trade-off between social benefits and privacy harms (Cf. section 6.1.3). The model by De and Imine seems to be a much needed tool today, as it has proven to be able help individuals manage their privacy settings, which might help them to better navigate in today’s complex networked privacy.
In regard to the cultural criteria in the CPM theory, the study by Li et al. (2017) helped
to discuss why some participants in group two seemed to feel threatened by those who are well versed
within technology and machine learning (Cf. section 6.1.4). The study by Li et al. (2017) indicates that this pattern might be explained due to the Danish culture norm of having a very low acceptance for ‘Power Distance’. Thus the Danish participants might, compared to other national cultures, tend to feel that authorities can infringe their privacy as they have a low tolerance for unequal distribution of influence or power.
Privacy Paradox in relation to the participants (Sub-question six)
Concluding on sub-question six, the Privacy Paradox cannot be said to apply to either the younger adults or the older adults. The reasons have been discussed in relation to the four patterns under sub-question six (Cf. section 5.5.2), and are outlined in the following.
First, there did not seem to be any evidence that can confirm pattern one (Cf. section 5.5.2). However, Baruh et al. (2017) presented findings that both supported and rejected pattern one i.e. that it is true that those who have more privacy concerns also have lower privacy literacy.
In regard to pattern two, this pattern was rejected as Baruh et al. (2017) found that
‘Those with higher privacy literacy reported higher concern for privacy’.
The third pattern cannot be either confirmed or rejected as the study by Zeissig et al.
(2017) did not provide findings to illuminate this pattern. However, it was indicated that older adults were more confident about their privacy literacy skills than younger adults. Additionally, Zeissig et al. (2017) also found that older adults perceive privacy protection to be a more complex a matter than younger adults did.
Pattern four was also rejected with regard to both groups (Cf. section 6.2). First, in relation to the younger adults, it is concluded the Privacy Paradox does not apply, even though the younger adults in this paper revealed a sense of indolence. This is concluded as the study by Hargittai and Marwick (2016) explained that it is not paradoxical that young adults tend to share their information even though they exhibit a sense of indolence. The reason is that the young adults’
attempts to protect their data has proven to be insufficient as the online privacy has become very networked, which makes the young adults’ attempts to protect themselves inadequate (Hargittai and Marwick, 2016).
Secondly, the older adults in this paper also exhibited a behavior, which indicated a
sense of indolence as they did report privacy concerns however they did not exhibit any intentions to
protect their online privacy (Cf. section 6.2). Nevertheless, this paper will conclude that there are no
privacy paradox to report related to older adults, as the study by Zeissig et al. (2017) indicates that
there are no privacy paradox related to older adults. This is based on the finding by Zeissig et al., that
those who had more privacy concerns also tended to exhibit more protective behaviours.
In document
An Attitudinal Analysis of Privacy Concerns Related to AI and Data
(Sider 65-69)